Symbol-Level Precoding Design Based on Distance Preserving Constructive Interference Regions

In this paper, we investigate the symbol-level precoding (SLP) design problem in the downlink of a multiuser multiple-input single-output (MISO) channel. We consider generic constellations with any arbitrary shape and size, and confine ourselves to one of the main categories of constructive interference regions (CIR), namely, distance preserving CIR (DPCIR). We provide a comprehensive study of DPCIRs and derive some properties for these regions. Using these properties, we first show that any signal in a given DPCIR has a norm greater than or equal to the norm of the corresponding constellation point if and only if the convex hull of the constellation contains the origin. It is followed by proving that the power of the noiseless received signal lying on a DPCIR is a monotonic strictly increasing function of two parameters relating to the infinite Voronoi edges. Using the convex description of DPCIRs and their properties, we formulate two design problems, namely, the SLP power minimization with signal-to-interference-plus-noise ratio (SINR) constraints, and the SLP SINR balancing problem under max-min fairness criterion. The SLP power minimization based on DPCIRs can straightforwardly be written as a quadratic program (QP). We provide a simplified reformulation of this problem which is less computationally complex. The SLP max-min SINR, however, is non-convex in its original form, and hence difficult to tackle. We propose several alternative optimization approaches, including semidefinite program (SDP) formulation and block coordinate descent (BCD) optimization. We discuss and evaluate the loss due to the proposed alternative methods through extensive simulation results.Comment: 19 pages, 12 figures, Submitted to IEEE Transactions in Signal Processin

Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area

Control-data separation architecture for cellular radio access networks: a survey and outlook

Conventional cellular systems are designed to ensure ubiquitous coverage with an always present wireless channel irrespective of the spatial and temporal demand of service. This approach raises several problems due to the tight coupling between network and data access points, as well as the paradigm shift towards data-oriented services, heterogeneous deployments and network densification. A logical separation between control and data planes is seen as a promising solution that could overcome these issues, by providing data services under the umbrella of a coverage layer. This article presents a holistic survey of existing literature on the control-data separation architecture (CDSA) for cellular radio access networks. As a starting point, we discuss the fundamentals, concepts, and general structure of the CDSA. Then, we point out limitations of the conventional architecture in futuristic deployment scenarios. In addition, we present and critically discuss the work that has been done to investigate potential benefits of the CDSA, as well as its technical challenges and enabling technologies. Finally, an overview of standardisation proposals related to this research vision is provided

Delay minimization for packet satellite communication systems.

Wong, Wing-ming Eric.Thesis (M.Phil.)--Chinese University of Hong Kong, 1990.Bibliography: leaves 46-47.ACKNOWLEDGMENTSABSTRACTChapter Chapter 1 --- INTRODUCTION --- p.1Chapter 1.1 --- Advantages and Disadvantages --- p.1Chapter 1.2 --- Satellite System Engineering --- p.2Chapter 1.3 --- Channel Allocation Methods --- p.3Chapter 1.4 --- Outline of this Thesis --- p.5Chapter Chapter 2 --- DELAY BOUNDS --- p.6Chapter 2.1 --- Introduction --- p.6Chapter 2.2 --- The Packet Satellite System --- p.7Chapter 2.3 --- The Idealized Protocol with Contention-Free Reservation --- p.8Chapter 2.4 --- Delay Lower Bound for Protocols with Contention-Free Reservation --- p.9Chapter 2.5 --- Delay Lower Bound for Protocols with Contention-Based Reservation --- p.14Chapter Chapter 3 --- IN SEARCH OF A MINIMUM DELAY PROTOCOL --- p.23Chapter 3.1 --- Introduction --- p.23Chapter 3.2 --- The Packet Satellite System --- p.25Chapter 3.3 --- The Transmission Protocol --- p.26Chapter 3.4 --- Throughput Analysis --- p.27Chapter 3.5 --- Delay Analysis --- p.28Chapter 3.6 --- Minimization of DI --- p.31Chapter 3.7 --- Minimization of DII --- p.38Chapter 3.8 --- Numerical Examples --- p.38Chapter Chapter 4 --- CONCLUSIONS --- p.45REFERENCES --- p.46APPENDIX --- p.4

A novel approach to MISO interference networks under maximum receive-power regulation

An aggressive frequency reuse is expected within the next years in order to increase the spectral ef¿ciency. Multiuser interference by all in-band transmitters can create a communication bottleneck and, therefore, it is compulsory to control it by means of radiated power regulations. In this work we consider received power as the main way to properly measure radiated power, serving at the same time as a spectrum sharing mechanism. Taking into account the constraints on the maximum total receive-power and maximum transmit-power, we ¿rst obtain the transmit powers that attain the Pareto-ef¿cient rates in an uncoordinated network. Among these rates, we identify the maximum sum-rate point for noise-limited scenarios. Next, in order to reach this working point using as less power as possible, we design a novel beamformer under some practical considerations. This beamformer can be calculated in a non-iterative and distributed fashion (i.e. transmitters do not need to exchange information). We evaluateour designby meansof Monte Carlosimulations, compare it with other non-iterative transmit beam formers and show its superior performance when the spectrum sharing receive-power constraints are imposed.Peer ReviewedPostprint (published version

Deep Learning Enabled Optimization of Downlink Beamforming Under Per-Antenna Power Constraints: Algorithms and Experimental Demonstration

This paper studies fast downlink beamforming algorithms using deep learning in multiuser multiple-input-single-output systems where each transmit antenna at the base station has its own power constraint. We focus on the signal-to-interference-plus-noise ratio (SINR) balancing problem which is quasi-convex but there is no efficient solution available. We first design a fast subgradient algorithm that can achieve near-optimal solution with reduced complexity. We then propose a deep neural network structure to learn the optimal beamforming based on convolutional networks and exploitation of the duality of the original problem. Two strategies of learning various dual variables are investigated with different accuracies, and the corresponding recovery of the original solution is facilitated by the subgradient algorithm. We also develop a generalization method of the proposed algorithms so that they can adapt to the varying number of users and antennas without re-training. We carry out intensive numerical simulations and testbed experiments to evaluate the performance of the proposed algorithms. Results show that the proposed algorithms achieve close to optimal solution in simulations with perfect channel information and outperform the alleged theoretically optimal solution in experiments, illustrating a better performance-complexity tradeoff than existing schemes