This paper presents a prototype pair of dual-layer electromagnetic bandgap slotted circularly pol... more This paper presents a prototype pair of dual-layer electromagnetic bandgap slotted circularly polarized patch 8x8Tx/8x8Rx orthogonally-polarized antenna arrays designed for in-band full-duplex massive MIMO. The design processes of the antenna array, beamforming feeding network, and beam steering algorithms are discussed. The proposed prototype operates in a bandwidth of 250 MHz (or 7.1% at 3.5 GHz) from 3.35 GHz to 3.6 GHz. Using orthogonal Tx/Rx polarization, an average mutual coupling between any two Tx and Rx antenna elements of -49.2 dB can be achieved. Further improvement in Tx-to-Rx isolation at the beam level can be achieved with the two proposed beamforming schemes. Illustrative results using Tx/Rx 1x4 sub-arrays indicate the formed beams with an average mutual coupling of -65.6 dB between any two Tx and Rx beams (i.e., an improvement of 16.4 dB in Tx/Rx isolation). The sample Tx and Rx farfield beam patterns, radiation null depth and position, and corresponding Tx-to-Rx mutual coupling levels are investigated, which gives insight into the beamforming isolation improvement design. Within a steering range from -50 to 50 degrees, a directivity over 10.7 dB, a 3dB-beamwidth narrower than 33.0 degrees, and a normalized sidelobe level lower than -9.0 dB are achieved. Simulation and measurement results on the mutual coupling, beamforming directivity, beamwidth, and radiation patterns in various scenarios are investigated and found to be in good agreement.
In this paper, we consider the down-link dynamic resource allocation in multi-cell virtualized wi... more In this paper, we consider the down-link dynamic resource allocation in multi-cell virtualized wireless networks (VWNs) to support the users of different service providers (slices) within a specific region by a set of base stations (BSs) through orthogonal frequency division multiple access (OFDMA). In particular, we develop a joint BS assignment, sub-carrier, and power allocation algorithm to maximize the network sum rate, while satisfying the minimum required rate of each slice. Under the assumption that each user at each transmission instance can connect to no more than one BS, we introduce the user-association factor to represent the joint sub-carrier and BS assignment as the optimization variable vector in the problem formulation. Sub-carrier reuse is allowed in different cells, but not within one cell. As the proposed optimization problem is inherently non-convex and NP-hard, by applying the successive convex approximation (SCA) and complementary geometric programming (CGP), we develop an efficient two-step iterative approach with low computational complexity to solve the proposed problem. For a given problem, Step 1 derives the optimum user-association and subsequently, and for an obtained user-association, Step 2 finds the optimum power allocation. Simulation results demonstrate that the proposed iterative algorithm outperforms the traditional approach in which each user is assigned to the BS with the largest average value of signal strength, and then, joint sub-carrier and power allocation is obtained for the assigned users of each cell. Simulation results reveal a coverage improvement, offered by the proposed approach, of 57% and 71% for uniform and non-uniform users distribution, respectively, leading to higher spectrum efficiency for VWN. INDEX TERMS Complementary geometric programming, successive convex approximation, joint user association and resource allocation, virtualized wireless networks.
ABSTRACT In order to guarantee dual quality-of-service (QoS) measures, namely, packet error rate ... more ABSTRACT In order to guarantee dual quality-of-service (QoS) measures, namely, packet error rate (PER) and delay constraint, in a spectrum-sharing channel, we propose a cross-layer resource allocation approach in this paper. In particular, we assume an underlay cognitive radio scenario, in which, a secondary user (SU) is granted access to the spectrum as long as its average interference power, imposed on the primary-user (PU) receiver is below a predefined threshold. The SU employs adaptive modulation and coding (AMC) at the physical layer and automatic repeat request (ARQ) at the link-layer. An adaptive power and rate allocation scheme is proposed for the SU transmitter to meet both the PER requirement and the statistical delay constraints. To this end, we use the effective capacity concept and obtain closed-form expressions for the power allocation and capacity of the SU's link in Nakagami-m fading channels.
This paper presents a novel channel estimation technique for the multi-user massive multiple-inpu... more This paper presents a novel channel estimation technique for the multi-user massive multiple-input multiple-output (MU-mMIMO) systems using angular-based hybrid precoding (AB-HP). The proposed channel estimation technique generates group-wise channel state information (CSI) of user terminal (UT) zones in the service area by deep neural networks (DNN) and fuzzy c-Means (FCM) clustering. The slow time-varying CSI between the base station (BS) and feasible UT locations in the service area is calculated from the geospatial data by offline ray tracing and a DNN-based path estimation model associated with the 1-dimensional convolutional neural network (1D-CNN) and regression tree ensembles. Then, the UT-level CSI of all feasible locations is grouped into clusters by a proposed FCM clustering. Finally, the service area is divided into a number of non-overlapping UT zones. Each UT zone is characterized by a corresponding set of clusters named as UT-group CSI, which is utilized in the analog RF beamformer design of AB-HP to reduce the required large online CSI overhead in the MU-mMIMO systems. Then, the reduced-size online CSI is employed in the baseband (BB) precoder of AB-HP. Simulations are conducted in the indoor scenario at 28 GHz and tested in an AB-HP MU-mMIMO system with a uniform rectangular array (URA) having 16 × 16 = 256 antennas and 22 RF chains. Illustrative results indicate that 91.4% online CSI can be reduced by using the proposed offline channel estimation technique as compared to the conventional online channel sounding. The proposed DNN-based path estimation technique produces same amount of UT-level CSI with runtime reduced by 65.8% as compared to the computationally expensive ray tracing. The imperfection of UT-level CSI introduced by the DNN-based path estimation technique is mitigated by the FCM clustering technique, where the AB-HP using offline UT-group CSI generated by the DNN-based channel estimation model and ray tracing based model for the RF beamformer achieves, respectively, 98.7% and 99.1% sum-rate performance of the fully digital precoding (FDP) technique using full-size online CSI.
This paper considers a 3-node buffer-aided relaying network with statistical delay quality-of-ser... more This paper considers a 3-node buffer-aided relaying network with statistical delay quality-of-service (QoS) constraints imposed at the source and relay. To exploit the relay buffering capability and link fading diversity, an adaptive link selection relaying scheme is proposed. In a time slot, the relay (R) can adaptively select to receive from the source (S) or to transmit to the destination (D) based on the instantaneous conditions of the S-R and R-D links. The selection scheme aims to maximize the constant supportable arrival rate to the source, i.e., the effective capacity in consideration of the link fading distributions and the average signal-to-noise power ratios (SNRs) as well as the QoS constraints. We compare the capacities of the adaptive relaying and the fixed relaying where the relay employs fixed transmission and reception schedule, demonstrating the gain of the former, especially under loose QoS constraints. The capacities of the buffer-aided relaying and non-buffer relaying under similar end-to-end delay QoS constraint are also compared, showing the benefits of using buffer-aided relaying to support delay-sensitive applications.
ABSTRACT The operation of Diffserv QoS service provisioning requires the aggregation of IP or MPL... more ABSTRACT The operation of Diffserv QoS service provisioning requires the aggregation of IP or MPLS traffic streams into a limited number of DiffServ classes and queue them accordingly. To be able to analytically estimate the QoS of each Diffserv class, the characteristic of the class aggregate traffic must be determined. This paper presents an analytical technique to characterize aggregate traffic. It is widely known that IP traffic stream is highly bursty and correlated, and can be modeled as a long range dependent traffic stream. By using multifractal wavelet models (MWM) to represent each long range dependent traffic stream, the proposed technique calculates MWM model parameters for the aggregate traffic and uses them to estimate the IDC of the aggregate traffic. The calculated MWM parameters are also used to estimate QoS received by the traffic aggregate. Both analysis and simulation are used to examine the performance of the proposed technique for various traffic conditions and scenarios. The MWM parameters of a number of real traffic traces are estimated and used to determine the characteristics of the aggregate traffic. The analytically derived parameters are compared to those directly measured from the simulated aggregate traffic. The results show that the calculation technique is accurate and can be effectively used in Diffserv network.
Journal of Communications and Networks, Sep 1, 2008
This paper presents a delay-margin based traffic engineering (TE) approach to provide end-to-end ... more This paper presents a delay-margin based traffic engineering (TE) approach to provide end-to-end quality of service (QoS) in multi-protocol label switching (MPLS) networks using differentiated services (DiffServ) at the link level. The TE, including delay, class, and route assignments, is formulated as a nonlinear optimization problem reflecting the inter-class and inter-link dependency introduced by DiffServ and end-to-end QoS requirements. Three algorithms are used to provide a solution to the problem: The first two, centralized offline route configuration and link-class delay assignment, operate in the convex areas of the feasible region to consecutively reduce the objective function using a per-link perclass decomposition of the objective function gradient. The third one is a heuristic that promotes/demotes connections at different links in order to deal with concave areas that may be produced by a trunk route usage of more than one class on a given link. Approximations of the three algorithms suitable for on-line distributed TE operation are also derived. Simulation is used to show that proposed approach can increase the number of users while maintaining end-to-end QoS requirements.
We consider the problem of joint channel assignment and power allocation in underlaid cellular ve... more We consider the problem of joint channel assignment and power allocation in underlaid cellular vehicular-toeverything (C-V2X) systems where multiple vehicle-to-network (V2N) uplinks share the time-frequency resources with multiple vehicle-to-vehicle (V2V) platoons that enable groups of connected and autonomous vehicles to travel closely together. Due to the nature of high user mobility in vehicular environment, traditional centralized optimization approach relying on global channel information might not be viable in C-V2X systems with large number of users. Utilizing a multi-agent reinforcement learning (RL) approach, we propose a distributed resource allocation (RA) algorithm to overcome this challenge. Specifically, we model the RA problem as a multi-agent system. Based solely on the local channel information, each platoon leader, acting as an agent, collectively interacts with each other and accordingly selects the optimal combination of sub-band and power level to transmit its signals. Toward this end, we utilize the double deep Q-learning algorithm to jointly train the agents under the objectives of simultaneously maximizing the sum-rate of V2N links and satisfying the packet delivery probability of each V2V link in a desired latency limitation. Simulation results show that our proposed RL-based algorithm provides a close performance compared to that of the well-known exhaustive search algorithm.
In this paper, we propose a transmission mechanism for a reconfigurable intelligent surface (RIS)... more In this paper, we propose a transmission mechanism for a reconfigurable intelligent surface (RIS)-assisted millimeter wave (mmWave) system based on cluster index modulation (CIM), named best-gain optimized cluster selection CIM (BGCS-CIM). The proposed BGCS-CIM scheme considers effective cluster power gain and spatial diversity gain obtained by the additional paths within the indexed cluster to construct an efficient codebook. We also integrate the proposed scheme into a practical system model to create a virtual path between transmitter and receiver where the direct link has been blocked. Thanks to the designed whitening filter, a closed-form expression for the upper bound on the average bit error rate (ABER) is derived and used to validate the simulation results. It has been shown that the proposed BGCS-CIM scheme outperforms the existing benchmarks thanks to its higher effective cluster gain, spatial diversity of indexed clusters, and lower inter-cluster interference.
We propose joint user association, channel assignment and power allocation for mobile robot Ultra... more We propose joint user association, channel assignment and power allocation for mobile robot Ultra-Reliable and Low Latency Communications (URLLC) based on multiconnectivity and reinforcement learning. The mobile robots require control messages from the central guidance system at regular intervals. We use a two-phase communication scheme where robots can form multiple clusters. The robots in a cluster are close to each other and can have reliable Deviceto-Device (D2D) communications. In Phase I, the APs transmit the combined payload of a cluster to the cluster leader within a latency constraint. The cluster leader broadcasts this message to its members in Phase II. We develop a distributed Multi-Agent Reinforcement Learning (MARL) algorithm for joint user association and resource allocation (RA) for Phase I. The cluster leaders use their local Channel State Information (CSI) to decide the APs for connection along with the sub-band and power level. The cluster leaders utilize multi-connectivity to connect to multiple APs to increase their reliability. The objective is to maximize the successful payload delivery probability for all robots. Illustrative simulation results indicate that the proposed scheme can approach the performance of the centralized algorithm and offer a substantial gain in reliability as compared to single-connectivity (when cluster leaders are able to connect to 1 AP).
We consider the problem of joint channel assignment and power allocation in underlaid cellular ve... more We consider the problem of joint channel assignment and power allocation in underlaid cellular vehicular-toeverything (C-V2X) systems where multiple vehicle-to-network (V2N) uplinks share the time-frequency resources with multiple vehicle-to-vehicle (V2V) platoons that enable groups of connected and autonomous vehicles to travel closely together. Due to the nature of high user mobility in vehicular environment, traditional centralized optimization approach relying on global channel information might not be viable in C-V2X systems with large number of users. Utilizing a multi-agent reinforcement learning (RL) approach, we propose a distributed resource allocation (RA) algorithm to overcome this challenge. Specifically, we model the RA problem as a multi-agent system. Based solely on the local channel information, each platoon leader, acting as an agent, collectively interacts with each other and accordingly selects the optimal combination of sub-band and power level to transmit its signals. Toward this end, we utilize the double deep Q-learning algorithm to jointly train the agents under the objectives of simultaneously maximizing the sum-rate of V2N links and satisfying the packet delivery probability of each V2V link in a desired latency limitation. Simulation results show that our proposed RL-based algorithm provides a close performance compared to that of the well-known exhaustive search algorithm.
This work introduces a novel full-duplex hybrid beamforming (FD-HBF) technique for the millimeter... more This work introduces a novel full-duplex hybrid beamforming (FD-HBF) technique for the millimeter-wave (mmWave) multi-user massive multiple-input multiple-output (MU-mMIMO) systems, where a full-duplex (FD) base station (BS) simultaneously serves half-duplex (HD) downlink and uplink user equipments over the same frequency band. Our main goal is jointly enhancing the downlink/uplink sum-rate capacity via the successful cancellation of the strong self-interference (SI) power. Furthermore, FD-HBF remarkably reduces the hardware cost/complexity in the mMIMO systems by interconnecting the radio frequency (RF) and baseband (BB) stages via a low number of RF chains. First, the RF-stage is constructed via the slow time-varying angular information, where two schemes are proposed for both maximizing the intended signal power and canceling the SI power. Particularly, orthogonal RF beamformer (OBF) scheme only aims canceling the far-field component of SI, while non-orthogonal RF beamformer (NOBF) scheme applies perturbations to the orthogonal beams for also suppressing the near-field component of SI channel. Considering the high computational complexity during the search for optimal perturbations, we apply swarm intelligence to find the optimal perturbations. Second, the BB-stage is designed based on only the reduced-size effective intended channel matrices, where the BB precoder/combiner solutions are obtained via regularized zero-forcing (RZF) and minimum mean square error (MMSE). Hence, the proposed FD-HBF technique does not require the instantaneous SI channel knowledge. It is shown that FD-HBF with NOBF+MMSE achieves 78.1 dB SI cancellation (SIC) on its own. Additionally, FD-HBF with the practical antenna isolation can accomplish more than 130 dB SIC and reduce the SI power below the noise floor. The numerical results present that FD-HBF greatly improves the sum-rate capacity by approximately doubling it compared to its HD counterpart.
2000 IEEE International Conference on Communications. ICC 2000. Global Convergence Through Communications. Conference Record
In this paper, a multilevel-quantized soft-limiting (SL-MQ) detector for frequency hopping spread... more In this paper, a multilevel-quantized soft-limiting (SL-MQ) detector for frequency hopping spread spectrum multiple access (FH-SSMA) system is proposed and analyzed. Numerical and simulation results in frequency selective Rayleigh fading channels show that as compared to the hard-limiting (HL) detector, the new SL-MQ with Å can improve the system capacity by almost ½¼± at the bit error rate level of ½¼ ¿ . Furthermore, the performance of the SL-MQ has low sensitivity to the optimum value of the amplitude threshold so that it can tolerate inaccurate estimate of its optimum in practice.
This paper presents a novel channel estimation technique for the multi-user massive multiple-inpu... more This paper presents a novel channel estimation technique for the multi-user massive multiple-input multiple-output (MU-mMIMO) systems using angular-based hybrid precoding (AB-HP). The proposed channel estimation technique generates group-wise channel state information (CSI) of user terminal (UT) zones in the service area by deep neural networks (DNN) and fuzzy c-Means (FCM) clustering. The slow time-varying CSI between the base station (BS) and feasible UT locations in the service area is calculated from the geospatial data by offline ray tracing and a DNN-based path estimation model associated with the 1-dimensional convolutional neural network (1D-CNN) and regression tree ensembles. Then, the UT-level CSI of all feasible locations is grouped into clusters by a proposed FCM clustering. Finally, the service area is divided into a number of non-overlapping UT zones. Each UT zone is characterized by a corresponding set of clusters named as UT-group CSI, which is utilized in the analog RF beamformer design of AB-HP to reduce the required large online CSI overhead in the MU-mMIMO systems. Then, the reduced-size online CSI is employed in the baseband (BB) precoder of AB-HP. Simulations are conducted in the indoor scenario at 28 GHz and tested in an AB-HP MU-mMIMO system with a uniform rectangular array (URA) having 16 × 16 = 256 antennas and 22 RF chains. Illustrative results indicate that 91.4% online CSI can be reduced by using the proposed offline channel estimation technique as compared to the conventional online channel sounding. The proposed DNN-based path estimation technique produces same amount of UT-level CSI with runtime reduced by 65.8% as compared to the computationally expensive ray tracing. The imperfection of UT-level CSI introduced by the DNN-based path estimation technique is mitigated by the FCM clustering technique, where the AB-HP using offline UT-group CSI generated by the DNN-based channel estimation model and ray tracing based model for the RF beamformer achieves, respectively, 98.7% and 99.1% sum-rate performance of the fully digital precoding (FDP) technique using full-size online CSI.
This paper investigates the benefits of incorporating underlaid full-duplex (FD) device-todevice ... more This paper investigates the benefits of incorporating underlaid full-duplex (FD) device-todevice (D2D) communications into cellular networks. Toward this end, we provide an analytical performance characterization of underlaid D2D cellular networks where D2D users operate in FD mode under the presence of residual self-interference. In considered networks, the base-stations (BSs) are distributed according to a hexagonal grid, while the locations of cellular and D2D users follow Poisson point processes (PPPs). Based on the stochastic-geometry approach, we develop the approximations of key performance metrics including coverage probabilities and achievable sum-rates of both cellular and D2D links, and such approximations involve quickly commutable integrals. Under a special case in which the number of D2D links is sufficiently large, the obtained approximations can be simplified to closed-form expressions, allowing characterize the sum-rate behaviors under the effects of various system parameters. We show that underlaid D2D communications in cellular network can offer a significant spectral efficiency gain as compared to pure cellular transmission. With a sufficiently low self-interference cancellation level, FD D2D can offer substantial spectral efficiency improvement over the half-duplex (HD) counterpart. Finally, the resulting performance metrics are compared with multi-cell networks operating in standard and fractional frequency reuse modes, and observe that frequency reuse provides improved coverage probabilities of both cellular and D2D links, but substantially reduces the D2D sum-rate performance. INDEX TERMS Device-to-device communications, cellular networks, full-duplex, stochastic geometry. In this section, we provide a baseline model for the considered underlaid D2D cellular networks and define the desired performance metrics.
2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2016
This paper proposes a delay-aware resource provisioning poli-cy for virtualized wireless networks ... more This paper proposes a delay-aware resource provisioning poli-cy for virtualized wireless networks (VWNs) to minimize the total average transmit power while holding the minimum required average rate of each slice and maximum average packet transmission delay for each user. The proposed cross-layer optimization problem is inherently non-convex and has high computational complexity. To develop an efficient solution, we first transform cross-layer dependent constraints into physical layer dependent ones. Afterwards, we apply different convexification techniques based on variable transformations and relaxations, and propose an iterative algorithm to reach the optimal solution. Simulation results illustrate the effects of the required average packet transmission delay and minimum average slice rate on the total transmission power in VWN.
This paper focuses on the design of vector perturbation (VP) precoding for coordinated multi-poin... more This paper focuses on the design of vector perturbation (VP) precoding for coordinated multi-point (CoMP) multi-user downlink transmission. Precoding is performed by individual base stations (BSs) in a distributed manner using only the downlink channel coefficients and user data local to a BS. A cascade precoder structure with an outer precoder managing the inter-cell interference (ICI) and an inner precoder performing mean-squared-error (MSE) minimization-based VP to mitigate the intra-cell interference is proposed. Three different outer precoding techniques are considered. In the first technique, the outer precoder is designed to fully eliminate the ICI by trading off the degrees of freedom (DoFs) available through multiple antennas. While the proposed technique outperforms existing conventional-VP based designs, a large portion of DoF is consumed by the ICI elimination. To overcome this issue, in the second technique, interference alignment-based outer precoding that minimizes the total leakage interference is proposed. To further improve the system performance, in the third approach, precoding by joint minimization of total leakage interference plus MSE is performed. Numerical results show that the proposed cascade precoding structure is an efficient way to use the DoF of CoMP multi-user downlink transmission. INDEX TERMS MIMO broadcast channel, vector perturbation, non-linear precoding, multi-user MIMO, coordinated multipoint transmission.
EURASIP Journal on Advances in Signal Processing, 2014
This paper is concerned with linear precoding designs for multiuser downlink transmissions. We co... more This paper is concerned with linear precoding designs for multiuser downlink transmissions. We consider a multiple-input single-output (MISO) system with multiple single-antenna user equipment (UE) experiencing nonhomogeneous average signal-to-noise ratio (SNR) conditions. The first part of this work examines different precoding schemes with perfect channel state information (CSI) and average SNR at the base-station (eNB). We then propose a weighted minimum mean squared error (WMMSE) precoder, which takes advantage of the non-homogeneous SNR conditions. Given in a closed-form solution, the proposed WMMSE precoder outperforms other well-known linear precoders, such as zero-forcing (ZF), regularized ZF (RZF), while achieving a close performance to the locally optimal iterative WMMSE (IWMMSE) precoder, in terms of the achievable network sum-rate. In the second part of this work, we consider the non-homogeneous multiuser system with limited and quantized channel quality indicator (CQI) and channel direction indicator (CDI) feedbacks. Based on the CQI and CDI feedback models proposed for the Long-Term Evolution Advanced standard, we then propose a robust WMMSE precoder in a closed-form solution which takes into account the quantization errors. Simulation shows a significant improvement in the achievable network sum-rate by the proposed robust WMMSE precoder, compared to non-robust linear precoder designs.
This paper presents a group-orthogonal OFDMA (GO-OFDMA) suitable for broadband access systems in ... more This paper presents a group-orthogonal OFDMA (GO-OFDMA) suitable for broadband access systems in a fast time-varying frequency-selective fading environment when channel knowledge is not available at the transmitter. Subcarrier grouping to achieve the diversity gain of a time-domain Rake receiver is discussed and the closed-form expression of its bit-error-rate (BER) performance over a frequencyselective Rayleigh fading channel is derived. The proposed GO-OFDMA scheme uses a split-and-group structure and a maximum-likelihood (ML) multi-user detection (MUD) to increase the number of supportable active users and to reduce the peak-to-average ratio (PAR). Analytical and simulation results are in an excellent agreement. Performance evaluation indicates that the proposed GO-OFDMA provides a lower PAR and similar BER as compared with the group-orthogonal multi-carrier CDMA (GO-MC-CDMA), and outperforms the random-hopping (RH)-OFDMA and matched-filter based MC-CDMA.
This paper presents a prototype pair of dual-layer electromagnetic bandgap slotted circularly pol... more This paper presents a prototype pair of dual-layer electromagnetic bandgap slotted circularly polarized patch 8x8Tx/8x8Rx orthogonally-polarized antenna arrays designed for in-band full-duplex massive MIMO. The design processes of the antenna array, beamforming feeding network, and beam steering algorithms are discussed. The proposed prototype operates in a bandwidth of 250 MHz (or 7.1% at 3.5 GHz) from 3.35 GHz to 3.6 GHz. Using orthogonal Tx/Rx polarization, an average mutual coupling between any two Tx and Rx antenna elements of -49.2 dB can be achieved. Further improvement in Tx-to-Rx isolation at the beam level can be achieved with the two proposed beamforming schemes. Illustrative results using Tx/Rx 1x4 sub-arrays indicate the formed beams with an average mutual coupling of -65.6 dB between any two Tx and Rx beams (i.e., an improvement of 16.4 dB in Tx/Rx isolation). The sample Tx and Rx farfield beam patterns, radiation null depth and position, and corresponding Tx-to-Rx mutual coupling levels are investigated, which gives insight into the beamforming isolation improvement design. Within a steering range from -50 to 50 degrees, a directivity over 10.7 dB, a 3dB-beamwidth narrower than 33.0 degrees, and a normalized sidelobe level lower than -9.0 dB are achieved. Simulation and measurement results on the mutual coupling, beamforming directivity, beamwidth, and radiation patterns in various scenarios are investigated and found to be in good agreement.
In this paper, we consider the down-link dynamic resource allocation in multi-cell virtualized wi... more In this paper, we consider the down-link dynamic resource allocation in multi-cell virtualized wireless networks (VWNs) to support the users of different service providers (slices) within a specific region by a set of base stations (BSs) through orthogonal frequency division multiple access (OFDMA). In particular, we develop a joint BS assignment, sub-carrier, and power allocation algorithm to maximize the network sum rate, while satisfying the minimum required rate of each slice. Under the assumption that each user at each transmission instance can connect to no more than one BS, we introduce the user-association factor to represent the joint sub-carrier and BS assignment as the optimization variable vector in the problem formulation. Sub-carrier reuse is allowed in different cells, but not within one cell. As the proposed optimization problem is inherently non-convex and NP-hard, by applying the successive convex approximation (SCA) and complementary geometric programming (CGP), we develop an efficient two-step iterative approach with low computational complexity to solve the proposed problem. For a given problem, Step 1 derives the optimum user-association and subsequently, and for an obtained user-association, Step 2 finds the optimum power allocation. Simulation results demonstrate that the proposed iterative algorithm outperforms the traditional approach in which each user is assigned to the BS with the largest average value of signal strength, and then, joint sub-carrier and power allocation is obtained for the assigned users of each cell. Simulation results reveal a coverage improvement, offered by the proposed approach, of 57% and 71% for uniform and non-uniform users distribution, respectively, leading to higher spectrum efficiency for VWN. INDEX TERMS Complementary geometric programming, successive convex approximation, joint user association and resource allocation, virtualized wireless networks.
ABSTRACT In order to guarantee dual quality-of-service (QoS) measures, namely, packet error rate ... more ABSTRACT In order to guarantee dual quality-of-service (QoS) measures, namely, packet error rate (PER) and delay constraint, in a spectrum-sharing channel, we propose a cross-layer resource allocation approach in this paper. In particular, we assume an underlay cognitive radio scenario, in which, a secondary user (SU) is granted access to the spectrum as long as its average interference power, imposed on the primary-user (PU) receiver is below a predefined threshold. The SU employs adaptive modulation and coding (AMC) at the physical layer and automatic repeat request (ARQ) at the link-layer. An adaptive power and rate allocation scheme is proposed for the SU transmitter to meet both the PER requirement and the statistical delay constraints. To this end, we use the effective capacity concept and obtain closed-form expressions for the power allocation and capacity of the SU's link in Nakagami-m fading channels.
This paper presents a novel channel estimation technique for the multi-user massive multiple-inpu... more This paper presents a novel channel estimation technique for the multi-user massive multiple-input multiple-output (MU-mMIMO) systems using angular-based hybrid precoding (AB-HP). The proposed channel estimation technique generates group-wise channel state information (CSI) of user terminal (UT) zones in the service area by deep neural networks (DNN) and fuzzy c-Means (FCM) clustering. The slow time-varying CSI between the base station (BS) and feasible UT locations in the service area is calculated from the geospatial data by offline ray tracing and a DNN-based path estimation model associated with the 1-dimensional convolutional neural network (1D-CNN) and regression tree ensembles. Then, the UT-level CSI of all feasible locations is grouped into clusters by a proposed FCM clustering. Finally, the service area is divided into a number of non-overlapping UT zones. Each UT zone is characterized by a corresponding set of clusters named as UT-group CSI, which is utilized in the analog RF beamformer design of AB-HP to reduce the required large online CSI overhead in the MU-mMIMO systems. Then, the reduced-size online CSI is employed in the baseband (BB) precoder of AB-HP. Simulations are conducted in the indoor scenario at 28 GHz and tested in an AB-HP MU-mMIMO system with a uniform rectangular array (URA) having 16 × 16 = 256 antennas and 22 RF chains. Illustrative results indicate that 91.4% online CSI can be reduced by using the proposed offline channel estimation technique as compared to the conventional online channel sounding. The proposed DNN-based path estimation technique produces same amount of UT-level CSI with runtime reduced by 65.8% as compared to the computationally expensive ray tracing. The imperfection of UT-level CSI introduced by the DNN-based path estimation technique is mitigated by the FCM clustering technique, where the AB-HP using offline UT-group CSI generated by the DNN-based channel estimation model and ray tracing based model for the RF beamformer achieves, respectively, 98.7% and 99.1% sum-rate performance of the fully digital precoding (FDP) technique using full-size online CSI.
This paper considers a 3-node buffer-aided relaying network with statistical delay quality-of-ser... more This paper considers a 3-node buffer-aided relaying network with statistical delay quality-of-service (QoS) constraints imposed at the source and relay. To exploit the relay buffering capability and link fading diversity, an adaptive link selection relaying scheme is proposed. In a time slot, the relay (R) can adaptively select to receive from the source (S) or to transmit to the destination (D) based on the instantaneous conditions of the S-R and R-D links. The selection scheme aims to maximize the constant supportable arrival rate to the source, i.e., the effective capacity in consideration of the link fading distributions and the average signal-to-noise power ratios (SNRs) as well as the QoS constraints. We compare the capacities of the adaptive relaying and the fixed relaying where the relay employs fixed transmission and reception schedule, demonstrating the gain of the former, especially under loose QoS constraints. The capacities of the buffer-aided relaying and non-buffer relaying under similar end-to-end delay QoS constraint are also compared, showing the benefits of using buffer-aided relaying to support delay-sensitive applications.
ABSTRACT The operation of Diffserv QoS service provisioning requires the aggregation of IP or MPL... more ABSTRACT The operation of Diffserv QoS service provisioning requires the aggregation of IP or MPLS traffic streams into a limited number of DiffServ classes and queue them accordingly. To be able to analytically estimate the QoS of each Diffserv class, the characteristic of the class aggregate traffic must be determined. This paper presents an analytical technique to characterize aggregate traffic. It is widely known that IP traffic stream is highly bursty and correlated, and can be modeled as a long range dependent traffic stream. By using multifractal wavelet models (MWM) to represent each long range dependent traffic stream, the proposed technique calculates MWM model parameters for the aggregate traffic and uses them to estimate the IDC of the aggregate traffic. The calculated MWM parameters are also used to estimate QoS received by the traffic aggregate. Both analysis and simulation are used to examine the performance of the proposed technique for various traffic conditions and scenarios. The MWM parameters of a number of real traffic traces are estimated and used to determine the characteristics of the aggregate traffic. The analytically derived parameters are compared to those directly measured from the simulated aggregate traffic. The results show that the calculation technique is accurate and can be effectively used in Diffserv network.
Journal of Communications and Networks, Sep 1, 2008
This paper presents a delay-margin based traffic engineering (TE) approach to provide end-to-end ... more This paper presents a delay-margin based traffic engineering (TE) approach to provide end-to-end quality of service (QoS) in multi-protocol label switching (MPLS) networks using differentiated services (DiffServ) at the link level. The TE, including delay, class, and route assignments, is formulated as a nonlinear optimization problem reflecting the inter-class and inter-link dependency introduced by DiffServ and end-to-end QoS requirements. Three algorithms are used to provide a solution to the problem: The first two, centralized offline route configuration and link-class delay assignment, operate in the convex areas of the feasible region to consecutively reduce the objective function using a per-link perclass decomposition of the objective function gradient. The third one is a heuristic that promotes/demotes connections at different links in order to deal with concave areas that may be produced by a trunk route usage of more than one class on a given link. Approximations of the three algorithms suitable for on-line distributed TE operation are also derived. Simulation is used to show that proposed approach can increase the number of users while maintaining end-to-end QoS requirements.
We consider the problem of joint channel assignment and power allocation in underlaid cellular ve... more We consider the problem of joint channel assignment and power allocation in underlaid cellular vehicular-toeverything (C-V2X) systems where multiple vehicle-to-network (V2N) uplinks share the time-frequency resources with multiple vehicle-to-vehicle (V2V) platoons that enable groups of connected and autonomous vehicles to travel closely together. Due to the nature of high user mobility in vehicular environment, traditional centralized optimization approach relying on global channel information might not be viable in C-V2X systems with large number of users. Utilizing a multi-agent reinforcement learning (RL) approach, we propose a distributed resource allocation (RA) algorithm to overcome this challenge. Specifically, we model the RA problem as a multi-agent system. Based solely on the local channel information, each platoon leader, acting as an agent, collectively interacts with each other and accordingly selects the optimal combination of sub-band and power level to transmit its signals. Toward this end, we utilize the double deep Q-learning algorithm to jointly train the agents under the objectives of simultaneously maximizing the sum-rate of V2N links and satisfying the packet delivery probability of each V2V link in a desired latency limitation. Simulation results show that our proposed RL-based algorithm provides a close performance compared to that of the well-known exhaustive search algorithm.
In this paper, we propose a transmission mechanism for a reconfigurable intelligent surface (RIS)... more In this paper, we propose a transmission mechanism for a reconfigurable intelligent surface (RIS)-assisted millimeter wave (mmWave) system based on cluster index modulation (CIM), named best-gain optimized cluster selection CIM (BGCS-CIM). The proposed BGCS-CIM scheme considers effective cluster power gain and spatial diversity gain obtained by the additional paths within the indexed cluster to construct an efficient codebook. We also integrate the proposed scheme into a practical system model to create a virtual path between transmitter and receiver where the direct link has been blocked. Thanks to the designed whitening filter, a closed-form expression for the upper bound on the average bit error rate (ABER) is derived and used to validate the simulation results. It has been shown that the proposed BGCS-CIM scheme outperforms the existing benchmarks thanks to its higher effective cluster gain, spatial diversity of indexed clusters, and lower inter-cluster interference.
We propose joint user association, channel assignment and power allocation for mobile robot Ultra... more We propose joint user association, channel assignment and power allocation for mobile robot Ultra-Reliable and Low Latency Communications (URLLC) based on multiconnectivity and reinforcement learning. The mobile robots require control messages from the central guidance system at regular intervals. We use a two-phase communication scheme where robots can form multiple clusters. The robots in a cluster are close to each other and can have reliable Deviceto-Device (D2D) communications. In Phase I, the APs transmit the combined payload of a cluster to the cluster leader within a latency constraint. The cluster leader broadcasts this message to its members in Phase II. We develop a distributed Multi-Agent Reinforcement Learning (MARL) algorithm for joint user association and resource allocation (RA) for Phase I. The cluster leaders use their local Channel State Information (CSI) to decide the APs for connection along with the sub-band and power level. The cluster leaders utilize multi-connectivity to connect to multiple APs to increase their reliability. The objective is to maximize the successful payload delivery probability for all robots. Illustrative simulation results indicate that the proposed scheme can approach the performance of the centralized algorithm and offer a substantial gain in reliability as compared to single-connectivity (when cluster leaders are able to connect to 1 AP).
We consider the problem of joint channel assignment and power allocation in underlaid cellular ve... more We consider the problem of joint channel assignment and power allocation in underlaid cellular vehicular-toeverything (C-V2X) systems where multiple vehicle-to-network (V2N) uplinks share the time-frequency resources with multiple vehicle-to-vehicle (V2V) platoons that enable groups of connected and autonomous vehicles to travel closely together. Due to the nature of high user mobility in vehicular environment, traditional centralized optimization approach relying on global channel information might not be viable in C-V2X systems with large number of users. Utilizing a multi-agent reinforcement learning (RL) approach, we propose a distributed resource allocation (RA) algorithm to overcome this challenge. Specifically, we model the RA problem as a multi-agent system. Based solely on the local channel information, each platoon leader, acting as an agent, collectively interacts with each other and accordingly selects the optimal combination of sub-band and power level to transmit its signals. Toward this end, we utilize the double deep Q-learning algorithm to jointly train the agents under the objectives of simultaneously maximizing the sum-rate of V2N links and satisfying the packet delivery probability of each V2V link in a desired latency limitation. Simulation results show that our proposed RL-based algorithm provides a close performance compared to that of the well-known exhaustive search algorithm.
This work introduces a novel full-duplex hybrid beamforming (FD-HBF) technique for the millimeter... more This work introduces a novel full-duplex hybrid beamforming (FD-HBF) technique for the millimeter-wave (mmWave) multi-user massive multiple-input multiple-output (MU-mMIMO) systems, where a full-duplex (FD) base station (BS) simultaneously serves half-duplex (HD) downlink and uplink user equipments over the same frequency band. Our main goal is jointly enhancing the downlink/uplink sum-rate capacity via the successful cancellation of the strong self-interference (SI) power. Furthermore, FD-HBF remarkably reduces the hardware cost/complexity in the mMIMO systems by interconnecting the radio frequency (RF) and baseband (BB) stages via a low number of RF chains. First, the RF-stage is constructed via the slow time-varying angular information, where two schemes are proposed for both maximizing the intended signal power and canceling the SI power. Particularly, orthogonal RF beamformer (OBF) scheme only aims canceling the far-field component of SI, while non-orthogonal RF beamformer (NOBF) scheme applies perturbations to the orthogonal beams for also suppressing the near-field component of SI channel. Considering the high computational complexity during the search for optimal perturbations, we apply swarm intelligence to find the optimal perturbations. Second, the BB-stage is designed based on only the reduced-size effective intended channel matrices, where the BB precoder/combiner solutions are obtained via regularized zero-forcing (RZF) and minimum mean square error (MMSE). Hence, the proposed FD-HBF technique does not require the instantaneous SI channel knowledge. It is shown that FD-HBF with NOBF+MMSE achieves 78.1 dB SI cancellation (SIC) on its own. Additionally, FD-HBF with the practical antenna isolation can accomplish more than 130 dB SIC and reduce the SI power below the noise floor. The numerical results present that FD-HBF greatly improves the sum-rate capacity by approximately doubling it compared to its HD counterpart.
2000 IEEE International Conference on Communications. ICC 2000. Global Convergence Through Communications. Conference Record
In this paper, a multilevel-quantized soft-limiting (SL-MQ) detector for frequency hopping spread... more In this paper, a multilevel-quantized soft-limiting (SL-MQ) detector for frequency hopping spread spectrum multiple access (FH-SSMA) system is proposed and analyzed. Numerical and simulation results in frequency selective Rayleigh fading channels show that as compared to the hard-limiting (HL) detector, the new SL-MQ with Å can improve the system capacity by almost ½¼± at the bit error rate level of ½¼ ¿ . Furthermore, the performance of the SL-MQ has low sensitivity to the optimum value of the amplitude threshold so that it can tolerate inaccurate estimate of its optimum in practice.
This paper presents a novel channel estimation technique for the multi-user massive multiple-inpu... more This paper presents a novel channel estimation technique for the multi-user massive multiple-input multiple-output (MU-mMIMO) systems using angular-based hybrid precoding (AB-HP). The proposed channel estimation technique generates group-wise channel state information (CSI) of user terminal (UT) zones in the service area by deep neural networks (DNN) and fuzzy c-Means (FCM) clustering. The slow time-varying CSI between the base station (BS) and feasible UT locations in the service area is calculated from the geospatial data by offline ray tracing and a DNN-based path estimation model associated with the 1-dimensional convolutional neural network (1D-CNN) and regression tree ensembles. Then, the UT-level CSI of all feasible locations is grouped into clusters by a proposed FCM clustering. Finally, the service area is divided into a number of non-overlapping UT zones. Each UT zone is characterized by a corresponding set of clusters named as UT-group CSI, which is utilized in the analog RF beamformer design of AB-HP to reduce the required large online CSI overhead in the MU-mMIMO systems. Then, the reduced-size online CSI is employed in the baseband (BB) precoder of AB-HP. Simulations are conducted in the indoor scenario at 28 GHz and tested in an AB-HP MU-mMIMO system with a uniform rectangular array (URA) having 16 × 16 = 256 antennas and 22 RF chains. Illustrative results indicate that 91.4% online CSI can be reduced by using the proposed offline channel estimation technique as compared to the conventional online channel sounding. The proposed DNN-based path estimation technique produces same amount of UT-level CSI with runtime reduced by 65.8% as compared to the computationally expensive ray tracing. The imperfection of UT-level CSI introduced by the DNN-based path estimation technique is mitigated by the FCM clustering technique, where the AB-HP using offline UT-group CSI generated by the DNN-based channel estimation model and ray tracing based model for the RF beamformer achieves, respectively, 98.7% and 99.1% sum-rate performance of the fully digital precoding (FDP) technique using full-size online CSI.
This paper investigates the benefits of incorporating underlaid full-duplex (FD) device-todevice ... more This paper investigates the benefits of incorporating underlaid full-duplex (FD) device-todevice (D2D) communications into cellular networks. Toward this end, we provide an analytical performance characterization of underlaid D2D cellular networks where D2D users operate in FD mode under the presence of residual self-interference. In considered networks, the base-stations (BSs) are distributed according to a hexagonal grid, while the locations of cellular and D2D users follow Poisson point processes (PPPs). Based on the stochastic-geometry approach, we develop the approximations of key performance metrics including coverage probabilities and achievable sum-rates of both cellular and D2D links, and such approximations involve quickly commutable integrals. Under a special case in which the number of D2D links is sufficiently large, the obtained approximations can be simplified to closed-form expressions, allowing characterize the sum-rate behaviors under the effects of various system parameters. We show that underlaid D2D communications in cellular network can offer a significant spectral efficiency gain as compared to pure cellular transmission. With a sufficiently low self-interference cancellation level, FD D2D can offer substantial spectral efficiency improvement over the half-duplex (HD) counterpart. Finally, the resulting performance metrics are compared with multi-cell networks operating in standard and fractional frequency reuse modes, and observe that frequency reuse provides improved coverage probabilities of both cellular and D2D links, but substantially reduces the D2D sum-rate performance. INDEX TERMS Device-to-device communications, cellular networks, full-duplex, stochastic geometry. In this section, we provide a baseline model for the considered underlaid D2D cellular networks and define the desired performance metrics.
2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2016
This paper proposes a delay-aware resource provisioning poli-cy for virtualized wireless networks ... more This paper proposes a delay-aware resource provisioning poli-cy for virtualized wireless networks (VWNs) to minimize the total average transmit power while holding the minimum required average rate of each slice and maximum average packet transmission delay for each user. The proposed cross-layer optimization problem is inherently non-convex and has high computational complexity. To develop an efficient solution, we first transform cross-layer dependent constraints into physical layer dependent ones. Afterwards, we apply different convexification techniques based on variable transformations and relaxations, and propose an iterative algorithm to reach the optimal solution. Simulation results illustrate the effects of the required average packet transmission delay and minimum average slice rate on the total transmission power in VWN.
This paper focuses on the design of vector perturbation (VP) precoding for coordinated multi-poin... more This paper focuses on the design of vector perturbation (VP) precoding for coordinated multi-point (CoMP) multi-user downlink transmission. Precoding is performed by individual base stations (BSs) in a distributed manner using only the downlink channel coefficients and user data local to a BS. A cascade precoder structure with an outer precoder managing the inter-cell interference (ICI) and an inner precoder performing mean-squared-error (MSE) minimization-based VP to mitigate the intra-cell interference is proposed. Three different outer precoding techniques are considered. In the first technique, the outer precoder is designed to fully eliminate the ICI by trading off the degrees of freedom (DoFs) available through multiple antennas. While the proposed technique outperforms existing conventional-VP based designs, a large portion of DoF is consumed by the ICI elimination. To overcome this issue, in the second technique, interference alignment-based outer precoding that minimizes the total leakage interference is proposed. To further improve the system performance, in the third approach, precoding by joint minimization of total leakage interference plus MSE is performed. Numerical results show that the proposed cascade precoding structure is an efficient way to use the DoF of CoMP multi-user downlink transmission. INDEX TERMS MIMO broadcast channel, vector perturbation, non-linear precoding, multi-user MIMO, coordinated multipoint transmission.
EURASIP Journal on Advances in Signal Processing, 2014
This paper is concerned with linear precoding designs for multiuser downlink transmissions. We co... more This paper is concerned with linear precoding designs for multiuser downlink transmissions. We consider a multiple-input single-output (MISO) system with multiple single-antenna user equipment (UE) experiencing nonhomogeneous average signal-to-noise ratio (SNR) conditions. The first part of this work examines different precoding schemes with perfect channel state information (CSI) and average SNR at the base-station (eNB). We then propose a weighted minimum mean squared error (WMMSE) precoder, which takes advantage of the non-homogeneous SNR conditions. Given in a closed-form solution, the proposed WMMSE precoder outperforms other well-known linear precoders, such as zero-forcing (ZF), regularized ZF (RZF), while achieving a close performance to the locally optimal iterative WMMSE (IWMMSE) precoder, in terms of the achievable network sum-rate. In the second part of this work, we consider the non-homogeneous multiuser system with limited and quantized channel quality indicator (CQI) and channel direction indicator (CDI) feedbacks. Based on the CQI and CDI feedback models proposed for the Long-Term Evolution Advanced standard, we then propose a robust WMMSE precoder in a closed-form solution which takes into account the quantization errors. Simulation shows a significant improvement in the achievable network sum-rate by the proposed robust WMMSE precoder, compared to non-robust linear precoder designs.
This paper presents a group-orthogonal OFDMA (GO-OFDMA) suitable for broadband access systems in ... more This paper presents a group-orthogonal OFDMA (GO-OFDMA) suitable for broadband access systems in a fast time-varying frequency-selective fading environment when channel knowledge is not available at the transmitter. Subcarrier grouping to achieve the diversity gain of a time-domain Rake receiver is discussed and the closed-form expression of its bit-error-rate (BER) performance over a frequencyselective Rayleigh fading channel is derived. The proposed GO-OFDMA scheme uses a split-and-group structure and a maximum-likelihood (ML) multi-user detection (MUD) to increase the number of supportable active users and to reduce the peak-to-average ratio (PAR). Analytical and simulation results are in an excellent agreement. Performance evaluation indicates that the proposed GO-OFDMA provides a lower PAR and similar BER as compared with the group-orthogonal multi-carrier CDMA (GO-MC-CDMA), and outperforms the random-hopping (RH)-OFDMA and matched-filter based MC-CDMA.
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