Max-min Fair Beamforming for SWIPT Systems with Non-linear EH Model

We study the beamforming design for multiuser systems with simultaneous wireless information and power transfer (SWIPT). Employing a practical non-linear energy harvesting (EH) model, the design is formulated as a non-convex optimization problem for the maximization of the minimum harvested power across several energy harvesting receivers. The proposed problem formulation takes into account imperfect channel state information (CSI) and a minimum required signal-to-interference-plus-noise ratio (SINR). The globally optimal solution of the design problem is obtained via the semidefinite programming (SDP) relaxation approach. Interestingly, we can show that at most one dedicated energy beam is needed to achieve optimality. Numerical results demonstrate that with the proposed design a significant performance gain and improved fairness can be provided to the users compared to two baseline schemes.Comment: Invited paper, IEEE VTC 2017, Fall, Toronto, Canad

Symbol-level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-art, Classification and Challenges

Precoding has been conventionally considered as an effective means of mitigating or exploiting the interference in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: i) transmitting distinct data streams to groups of users and ii) applying precoding on a symbol-per-symbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: i) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding, ii) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area

Robust Transmission in Downlink Multiuser MISO Systems: A Rate-Splitting Approach

We consider a downlink multiuser MISO system with bounded errors in the Channel State Information at the Transmitter (CSIT). We first look at the robust design problem of achieving max-min fairness amongst users (in the worst-case sense). Contrary to the conventional approach adopted in literature, we propose a rather unorthodox design based on a Rate-Splitting (RS) strategy. Each user's message is split into two parts, a common part and a private part. All common parts are packed into one super common message encoded using a public codebook, while private parts are independently encoded. The resulting symbol streams are linearly precoded and simultaneously transmitted, and each receiver retrieves its intended message by decoding both the common stream and its corresponding private stream. For CSIT uncertainty regions that scale with SNR (e.g. by scaling the number of feedback bits), we prove that a RS-based design achieves higher max-min (symmetric) Degrees of Freedom (DoF) compared to conventional designs (NoRS). For the special case of non-scaling CSIT (e.g. fixed number of feedback bits), and contrary to NoRS, RS can achieve a non-saturating max-min rate. We propose a robust algorithm based on the cutting-set method coupled with the Weighted Minimum Mean Square Error (WMMSE) approach, and we demonstrate its performance gains over state-of-the art designs. Finally, we extend the RS strategy to address the Quality of Service (QoS) constrained power minimization problem, and we demonstrate significant gains over NoRS-based designs.Comment: Accepted for publication in IEEE Transactions on Signal Processin

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

Smart antennas: state of the art

Aim of this contribution is to illustrate the state of the art of smart antenna research from several perspectives. The bow is drawn from transmitter issues via channel measurements and modeling, receiver signal processing, network aspects, technological challenges towards first smart antenna applications and current status of standardization. Moreover, some future prospects of different disciplines in smart antenna research are given.Peer Reviewe