A Rate-Splitting Strategy for Max-Min Fair Multigroup Multicasting

We consider the problem of transmit beamforming to multiple cochannel multicast groups. The conventional approach is to beamform a designated data stream to each group, while treating potential inter-group interference as noise at the receivers. In overloaded systems where the number of transmit antennas is insufficient to perform interference nulling, we show that inter-group interference dominates at high SNRs, leading to a saturating max-min fair performance. We propose a rather unconventional approach to cope with this issue based on the concept of Rate-Splitting (RS). In particular, part of the interference is broadcasted to all groups such that it is decoded and canceled before the designated beams are decoded. We show that the RS strategy achieves significant performance gains over the conventional multigroup multicast beamforming strategy.Comment: accepted to the 17th IEEE International workshop on Signal Processing advances in Wireless Communications (SPAWC 2016

Coordinated Multicasting with Opportunistic User Selection in Multicell Wireless Systems

Physical layer multicasting with opportunistic user selection (OUS) is examined for multicell multi-antenna wireless systems. By adopting a two-layer encoding scheme, a rate-adaptive channel code is applied in each fading block to enable successful decoding by a chosen subset of users (which varies over different blocks) and an application layer erasure code is employed across multiple blocks to ensure that every user is able to recover the message after decoding successfully in a sufficient number of blocks. The transmit signal and code-rate in each block determine opportunistically the subset of users that are able to successfully decode and can be chosen to maximize the long-term multicast efficiency. The employment of OUS not only helps avoid rate-limitations caused by the user with the worst channel, but also helps coordinate interference among different cells and multicast groups. In this work, efficient algorithms are proposed for the design of the transmit covariance matrices, the physical layer code-rates, and the target user subsets in each block. In the single group scenario, the system parameters are determined by maximizing the group-rate, defined as the physical layer code-rate times the fraction of users that can successfully decode in each block. In the multi-group scenario, the system parameters are determined by considering a group-rate balancing optimization problem, which is solved by a successive convex approximation (SCA) approach. To further reduce the feedback overhead, we also consider the case where only part of the users feed back their channel vectors in each block and propose a design based on the balancing of the expected group-rates. In addition to SCA, a sample average approximation technique is also introduced to handle the probabilistic terms arising in this problem. The effectiveness of the proposed schemes is demonstrated by computer simulations.Comment: Accepted by IEEE Transactions on Signal Processin

Sum Rate Maximizing Multigroup Multicast Beamforming under Per-antenna Power Constraints

A multi-antenna transmitter that conveys independent sets of common data to distinct groups of users is herein considered, a model known as physical layer multicasting to multiple co-channel groups. In the recently proposed context of per-antenna power constrained multigroup multicasting, the present work focuses on a novel system design that aims at maximizing the total achievable throughput. Towards increasing the system sum rate, the available power resources need to be allocated to well conditioned groups of users. A detailed solution to tackle the elaborate sum rate maximization multigroup multicast problem under per-antenna power constraints is therefore derived. Numerical results are presented to quantify the gains of the proposed algorithm over heuristic solutions. Besides Rayleigh faded channels, the solution is also applied to uniform linear array transmitters operating in the far field, where line-ofsight conditions are realized. In this setting, a sensitivity analysis with respect to the angular separation of co-group users is included. Finally, a simple scenario providing important intuitions for the sum rate maximizing multigroup multicast solutions is elaborated.Comment: Submitted to IEEE GlobeCom 2014, Austin, TX. arXiv admin note: substantial text overlap with arXiv:1406.7699, arXiv:1406.755

Coordinated Multicast Beamforming in Multicell Networks

We study physical layer multicasting in multicell networks where each base station, equipped with multiple antennas, transmits a common message using a single beamformer to multiple users in the same cell. We investigate two coordinated beamforming designs: the quality-of-service (QoS) beamforming and the max-min SINR (signal-to-interference-plus-noise ratio) beamforming. The goal of the QoS beamforming is to minimize the total power consumption while guaranteeing that received SINR at each user is above a predetermined threshold. We present a necessary condition for the optimization problem to be feasible. Then, based on the decomposition theory, we propose a novel decentralized algorithm to implement the coordinated beamforming with limited information sharing among different base stations. The algorithm is guaranteed to converge and in most cases it converges to the optimal solution. The max-min SINR (MMS) beamforming is to maximize the minimum received SINR among all users under per-base station power constraints. We show that the MMS problem and a weighted peak-power minimization (WPPM) problem are inverse problems. Based on this inversion relationship, we then propose an efficient algorithm to solve the MMS problem in an approximate manner. Simulation results demonstrate significant advantages of the proposed multicast beamforming algorithms over conventional multicasting schemes.Comment: 10pages, 9 figure

Massive MIMO Multicasting in Noncooperative Cellular Networks

We study the massive multiple-input multiple-output (MIMO) multicast transmission in cellular networks where each base station (BS) is equipped with a large-scale antenna array and transmits a common message using a single beamformer to multiple mobile users. We first show that when each BS knows the perfect channel state information (CSI) of its own served users, the asymptotically optimal beamformer at each BS is a linear combination of the channel vectors of its multicast users. Moreover, the optimal combining coefficients are obtained in closed form. Then we consider the imperfect CSI scenario where the CSI is obtained through uplink channel estimation in timedivision duplex systems. We propose a new pilot scheme that estimates the composite channel which is a linear combination of the individual channels of multicast users in each cell. This scheme is able to completely eliminate pilot contamination. The pilot power control for optimizing the multicast beamformer at each BS is also derived. Numerical results show that the asymptotic performance of the proposed scheme is close to the ideal case with perfect CSI. Simulation also verifies the effectiveness of the proposed scheme with finite number of antennas at each BS.Comment: to appear in IEEE JSAC Special Issue on 5G Wireless Communication System

Frame Based Precoding in Satellite Communications: A Multicast Approach

In the present work, a multibeam satellite that employs aggressive frequency reuse towards increasing the offered throughput is considered. Focusing on the forward link, the goal is to employ multi-antenna signal processing techniques, namely linear precoding, to manage the inter-beam interferences. In this context, fundamental practical limitations, namely the rigid framing structure of satellite communication standards and the on-board per-antenna power constraints, are herein considered. Therefore, the concept of optimal frame based precoding under per-antenna constraints, is discussed. This consists in precoding the transmit signals without changing the underlying framing structure of the communication standard. In the present work, the connection of the frame based precoding problem with the generic signal processing problem of conveying independent sets of common data to distinct groups of users is established. This model is known as physical layer multicasting to multiple co-channel groups. Building on recent results, the weighted fair per-antenna power constrained multigroup multicast precoders are employed for frame based precoding. The throughput performance of these solutions is compared to multicast aware heuristic precoding methods over a realistic multibeam satellite scenario. Consequently, the gains of the proposed approach are quantified via extensive numerical results.Comment: Accepted for presentation at the IEEE ASMS 201

Real Coded Genetic Algorithm with Enhanced Abilities for Adaptation Applied to Optimisation of MIMO Systems

This article presents an investigation of real coded Genetic Algorithm Blend Crossover Alpha modification, with enhanced ability for adaptation, applied to minimisation of transmit power in multiple-input multiple-output (MIMO) systems beamforming. The goal is to formulate transmit power minimisation task as a black box software object and evaluate an alternative to currently existing methods for optimisation of transmit energy in multicast system constrained by signal to noise ratio. The novelty of this adaptive methodology for determination of minimal power level within certain Quality of Service criteria is that it guarantees satisfaction of the constraint and 100% feasibility of achieved solutions. In addition this methodology excludes retuning algorithms parameters by using black box model for the problem definition. Experiments are conducted for identification of weight vectors assigned for signal strength and direction. Achieved experimental results are presented and analysed

Energy-Efficient Coordinated Multi-Cell Multigroup Multicast Beamforming with Antenna Selection

This paper studies energy-efficient coordinated beamforming in multi-cell multi-user multigroup multicast multiple-input single-output systems. We aim at maximizing the network energy efficiency by taking into account the fact that some of the radio frequency chains can be switched off in order to save power. We consider the antenna specific maximum power constraints to avoid non-linear distortion in power amplifiers and user-specific quality of service (QoS) constraints to guarantee a certain QoS levels. We first introduce binary antenna selection variables and use the perspective formulation to model the relation between them and the beamformers. Subsequently, we propose a new formulation which reduces the feasible set of the continuous relaxation, resulting in better performance compared to the original perspective formulation based problem. However, the resulting optimization problem is a mixed-Boolean non-convex fractional program, which is difficult to solve. We follow the standard continuous relaxation of the binary antenna selection variables, and then reformulate the problem such that it is amendable to successive convex approximation. Thereby, solving the continuous relaxation mostly results in near-binary solution. To recover the binary variables from the continuous relaxation, we switch off all the antennas for which the continuous values are smaller than a small threshold. Numerical results illustrate the superior convergence result and significant achievable gains in terms of energy efficiency with the proposed algorithm.Comment: 6 pages, 5 figures, accepted to IEEE ICC 2017 - International Workshop on 5G RAN Desig