Distributed Multicell Beamforming Design Approaching Pareto Boundary with Max-Min Fairness

This paper addresses coordinated downlink beamforming optimization in multicell time-division duplex (TDD) systems where a small number of parameters are exchanged between cells but with no data sharing. With the goal to reach the point on the Pareto boundary with max-min rate fairness, we first develop a two-step centralized optimization algorithm to design the joint beamforming vectors. This algorithm can achieve a further sum-rate improvement over the max-min optimal performance, and is shown to guarantee max-min Pareto optimality for scenarios with two base stations (BSs) each serving a single user. To realize a distributed solution with limited intercell communication, we then propose an iterative algorithm by exploiting an approximate uplink-downlink duality, in which only a small number of positive scalars are shared between cells in each iteration. Simulation results show that the proposed distributed solution achieves a fairness rate performance close to the centralized algorithm while it has a better sum-rate performance, and demonstrates a better tradeoff between sum-rate and fairness than the Nash Bargaining solution especially at high signal-to-noise ratio.Comment: 8 figures. To Appear in IEEE Trans. Wireless Communications, 201

Joint Beamforming and Power Control in Coordinated Multicell: Max-Min Duality, Effective Network and Large System Transition

This paper studies joint beamforming and power control in a coordinated multicell downlink system that serves multiple users per cell to maximize the minimum weighted signal-to-interference-plus-noise ratio. The optimal solution and distributed algorithm with geometrically fast convergence rate are derived by employing the nonlinear Perron-Frobenius theory and the multicell network duality. The iterative algorithm, though operating in a distributed manner, still requires instantaneous power update within the coordinated cluster through the backhaul. The backhaul information exchange and message passing may become prohibitive with increasing number of transmit antennas and increasing number of users. In order to derive asymptotically optimal solution, random matrix theory is leveraged to design a distributed algorithm that only requires statistical information. The advantage of our approach is that there is no instantaneous power update through backhaul. Moreover, by using nonlinear Perron-Frobenius theory and random matrix theory, an effective primal network and an effective dual network are proposed to characterize and interpret the asymptotic solution.Comment: Some typos in the version publised in the IEEE Transactions on Wireless Communications are correcte

Beamforming Techniques for Non-Orthogonal Multiple Access in 5G Cellular Networks

In this paper, we develop various beamforming techniques for downlink transmission for multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) systems. First, a beamforming approach with perfect channel state information (CSI) is investigated to provide the required quality of service (QoS) for all users. Taylor series approximation and semidefinite relaxation (SDR) techniques are employed to reformulate the original non-convex power minimization problem to a tractable one. Further, a fairness-based beamforming approach is proposed through a max-min formulation to maintain fairness between users. Next, we consider a robust scheme by incorporating channel uncertainties, where the transmit power is minimized while satisfying the outage probability requirement at each user. Through exploiting the SDR approach, the original non-convex problem is reformulated in a linear matrix inequality (LMI) form to obtain the optimal solution. Numerical results demonstrate that the robust scheme can achieve better performance compared to the non-robust scheme in terms of the rate satisfaction ratio. Further, simulation results confirm that NOMA consumes a little over half transmit power needed by OMA for the same data rate requirements. Hence, NOMA has the potential to significantly improve the system performance in terms of transmit power consumption in future 5G networks and beyond.Comment: accepted to publish in IEEE Transactions on Vehicular Technolog

Cooperative Transmission for Downlink Distributed Antenna in Time Division Duplex System

Multi-user distributed antenna system (MU-DAS) systems play the essential role in improving throughput performance in wireless communications. This improvement can be achieved by exploiting the spatial domain and without the need of additional power and bandwidth. In this thesis, three main issues which are of importance to the data rate transmission have been investigated. Firstly, user clustering in MU-DAS downlink systems has been considered, where this technique can be effciently used to reduce the complexity and cost caused by radio frequency chains, associated with antennas while keeping most of the diversity advantages of the system. The proposed user clustering algorithm which can select an optimal set of antennas for transmission. The capacity achieved by the proposed algorithm is almost same as the capacity of the optimum search method, with much lower complexity. Secondly, interference alignment in MU-DAS downlink systems has been studied. The inter-cluster interference is uncoordinated and limits the system performance. The inter-cluster interference should be eliminated or minimized carefully. The interference alignment is proposed to consolidate the strong inter-cluster interference into smaller dimensions of signal space at each user and use the remaining dimensions to transmit the desired signals without any interference. The performance of single cluster is better than the proposed algorithm due to the absence of intercluster interference in the single cluster. The numerical shows that the proposed algorithm is more suitable in multi-cell DAS environment due to the presence of inter-cell interference. Finally, the impact of different user mobility on TDD downlink MUDAS has been studied. The downlink data transmission in time division duplex (TDD) systems is optimized according to the channel state information (CSI) which is obtained at the uplink time slot. However, the actual channel at downlink time slot may be different from the estimated channel due to channel variation in mobility environment. Based on mobility state information (MSI), an autocorrelation based feedback interval adjustment technique is proposed. The proposed technique adjusts the CSI update interval and mitigates the performance degradation imposed by the user mobility and the transmission delay. Cooperative clusters are formed to maximize sum rate. In order to reduce the computational complexity, a channel gain based antenna selection and signal-to-interference plus noise ratio (SINR) based user clustering are developed. A downlink ergodic capacity is derived in single user clustering. The derived analytical expressions of the downlink ergodic capacity are verified by system simulations. Numerical results show that the proposed scheme can improved sum rate over the non cooperative system and no MSI knowledge. The proposed technique has good performance for a wide range of user speed and suitable for future wireless communications systems