A High-Diversity Transceiver Design for MISO Broadcast Channels

In this paper, the outage behavior and diversity order of the mixture transceiver architecture for multiple-input single-output broadcast channels are analyzed. The mixture scheme groups users with closely-aligned channels and applies superposition coding and successive interference cancellation decoding to each group composed of users with closely-aligned channels, while applying zero-forcing beamforming across semi-orthogonal user groups. In order to enable such analysis, closed-form lower bounds on the achievable rates of a general multiple-input single-output broadcast channel with superposition coding and successive interference cancellation are newly derived. By employing channel-adaptive user grouping and proper power allocation, which ensures that the channel subspaces of user groups have angle larger than a certain threshold, it is shown that the mixture transceiver architecture achieves full diversity order in multiple-input single-output broadcast channels and opportunistically increases the multiplexing gain while achieving full diversity order. Furthermore, the achieved full diversity order is the same as that of the single-user maximum ratio transmit beamforming. Hence, the mixture scheme can provide reliable communication under channel fading for ultra-reliable low latency communication. Numerical results validate our analysis and show the outage superiority of the mixture scheme over conventional transceiver designs for multiple-input single-output broadcast channels.Comment: The inner region is evaluated. The single-group SIC performance is evaluate

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

Spectrum Sharing in mmWave Cellular Networks via Cell Association, Coordination, and Beamforming

This paper investigates the extent to which spectrum sharing in mmWave networks with multiple cellular operators is a viable alternative to traditional dedicated spectrum allocation. Specifically, we develop a general mathematical framework by which to characterize the performance gain that can be obtained when spectrum sharing is used, as a function of the underlying beamforming, operator coordination, bandwidth, and infrastructure sharing scenarios. The framework is based on joint beamforming and cell association optimization, with the objective of maximizing the long-term throughput of the users. Our asymptotic and non-asymptotic performance analyses reveal five key points: (1) spectrum sharing with light on-demand intra- and inter-operator coordination is feasible, especially at higher mmWave frequencies (for example, 73 GHz), (2) directional communications at the user equipment substantially alleviate the potential disadvantages of spectrum sharing (such as higher multiuser interference), (3) large numbers of antenna elements can reduce the need for coordination and simplify the implementation of spectrum sharing, (4) while inter-operator coordination can be neglected in the large-antenna regime, intra-operator coordination can still bring gains by balancing the network load, and (5) critical control signals among base stations, operators, and user equipment should be protected from the adverse effects of spectrum sharing, for example by means of exclusive resource allocation. The results of this paper, and their extensions obtained by relaxing some ideal assumptions, can provide important insights for future standardization and spectrum policy.Comment: 15 pages. To appear in IEEE JSAC Special Issue on Spectrum Sharing and Aggregation for Future Wireless Network

System Level Simulation and Radio Resource Management for Distributed Antenna Systems with Cognitive Radio and Multi-Cell Cooperation

4th International Conference on Future Generation Communication Technologies (FGCT 2015), Luton, United Kingdom.The performance of wireless networks will experience a considerable improvement by the use of novel technologies such as distributed antenna systems (DASs), multi-cell cooperation (MCC), and cognitive radio (CR). These solutions have shown considerable gains at the physical-layer (PHY). However, several issues remain open in the system-level evaluation, radio resource management (RRM), and particularly in the design of billing/licensing schemes for this type of system. This paper proposes a system-level simulator (SLS) that will help in addressing these issues. The paper focuses on the description of the modules of a generic SLS that need a modification to cope with the new transmission/economic paradigms. An advanced RRM solution is proposed for a multi-cell DAS with two levels of cooperation: inside the cell (intra-cell) to coordinate the transmission of distributed nodes within the cell, and between cells (inter-cell or MCC) to adapt cell transmissions according to the collected inter-cell interference measurements. The RRM solution blends network and financial metrics using the theory of multiobjective portfolio optimization. The core of the RRM solution is an iterative weighted least squares (WLS) optimization algorithm that aims to schedule in a fair manner as many terminals as possible across all the radio resources of the available frequency bands (licensed and non-licensed), while considering different economic metrics. The RRM algorithm includes joint terminal scheduling, link adaptation, space division multiplexing, spectrum selection, and resource allocation