Multi-group multicast beamforming in cognitive radio networks via rank-two transmit beamformed Alamouti space-time coding

Abstract

In this paper, we consider transmit design in multiple-input singleoutput (MISO) multi-group multicast (MM) cognitive radio (CR) systems. Previously, semidefinite relaxation (SDR)-based transmit beamforming has been very successful in transmit design. However, recent research shows that further performance gain is possible by suitably modifying the transmit structure. Here, we propose a transmit beamformed Alamouti space-time code scheme for MM-CR systems, whose corresponding transmit design problem can be reformulated as a rank-2 constrained fractional semidefinite program. We then develop an SDR framework for this scheme and study its signal-to-interference-and-noise ratio (SINR) performance via both theoretical analysis and simulations. Specifically, we show that the worst-case approximation accuracy of the proposed scheme scales on the order of √ MS log MP , where MP (resp. MS) is the number of primary (resp. secondary) users in the CR network. This unifies and generalizes a number of results in the literature and is, to the best of our knowledge, the first provable bound on the performance of a beamforming scheme in a general MM-CR system. Finally, simulation results show that our proposed scheme indeed has a better performance in both MM and MM-CR scenarios than the traditional beamforming scheme.

Distributed Cooperative Multicast in Cognitive Multi-Relay Multi-Antenna Systems

“…Thus, the optimal forwarding policy design problem can be formulated as (9) Remark 1: 1) In our model, perfect timing and frequency synchronization is assumed [2] [3], and CSI about the interference channel is also assumed to be perfectly known at relay nodes [7][8]; 2) Different from [2][3], interference control for PNs is considered in our model. As a result, the design of the forwarding matrices is not only to balance the received signal power among different multicast users and mitigate the mutual interference among different multicast sessions (as shown in [2] [3]), but also to avoid large interference on primary users.…”

General Rank Multiuser Downlink Beamforming With Shaping Constraints Using Real-Valued OSTBC

“…We exploit CSI knowledge at the transmitter and combine downlink beamforming with full-rate high dimensional real-valued OSTBC to increase the degrees of freedom in the beamformer design. Several works have proposed the idea of combining beamforming with space time coding [28]- [37].…”

“…A similar approach of rank-two beamforming is proposed for single-group multicasting using a relay network in [35]. The concept of rank-two beamforming has later been extended in [36] and [37] to solve the multi-group multicast beamforming problem in which beamforming is used to simultaneously deliver independent data services to users in predefined subscriber groups.…”

“…The idea of combining beamforming with OSTBC in this work follows the general framework of [32]- [37] in which rank-two beamformers are designed in combination with the application of Alamouti coding [38]. In contrast to the rank-two beamformer designs in [32]- [37], we consider herein the downlink beamforming problem where each user is designed to be served by multiple beamformers combined with full-rate higher dimensional real-valued OSTBC.…”

“…Similarly, in the Alamouti coding based beamforming approaches of [32]- [37], rank reduction is applied if the SDR solution exhibits a rank greater than two. In our proposed real-valued OSTBC based beamforming approach, the SDR solution after the rank reduction procedure is proven to be optimal for the original problem if all ranks are no greater than eight.…”