Performance of distributed beamforming for dense relay deployments in the presence of limited feedback information
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RESEARCH
Open Access
Performance of distributed beamforming for dense relay deployments in the presence of limited feedback information Turo Halinen1* , Alexis A Dowhuszko1 and Jyri Hämäläinen1,2
Abstract This paper studies the impact of quantized channel feedback on the performance of a (coherent) distributed beamforming (DBF) scheme. The analysis is done in the context of a wireless access network, and the goal is to provide an adequate broadband coverage for users located inside buildings. In the examined scenario, instead of trying to reach the serving base station (BS) directly, we assume that each mobile user equipment (UE) receives assistance from a cooperative group of network elements that is placed in close proximity (e.g., in the same room or office). This cluster of cooperative network elements is formed by a large number of low-cost relaying stations (RSs), which have fixed locations and are equipped with only one antenna. To simplify the analysis, communication in the first hop (i.e., from the mobile UE to the elements of the cluster) is assumed practically costless, making the bottleneck lie in the second hop of the system (i.e., from the elements of the cluster to the serving BS). Closed-form approximations for three different performance measures are derived (i.e., outage probability, ergodic capacity, bit error probability), providing accurate predictions of the fundamental limits that proposed system architecture is able to provide. Our analysis reveals that the achievable end-to-end performance when using a small amount of phase feedback information (per RS in the second hop) is very close to the full phase information upper bound, paving the way to the use of massive DBF architectures as a practical way to cope with high data rate demands of future wireless systems. Keywords: Cooperative communications, Distributed beamforming, Decode-and-forward relays, Heterogeneous networks, Limited feedback information, Massive network element deployments, Non-perfect channel knowledge, Performance prediction
1 Introduction The demand of mobile data has been growing at a steady pace in the last few years, as the usage of new types of mobile devices such as smartphones and tablets has become a mainstream. This tendency has been also fueled by the introduction of new mobile applications, creating a new category of users that call for a better support of high data rates. It is not surprising that many independent sources have predicted a dramatic increase in mobile broadband traffic in the next few years [1]. In addition, by the year 2020, it is also expected that every one of us will be surrounded by an average number of 10 wirelessenabled devices, resulting in a 10-fold increase in the *Correspondence: [email protected] 1 Department of Communications and Networking, Aalto University, P.O. Box 13000, Aalto FI-00076, Finland Full list of author information is available at the end of the article
number of equipment that will admit wireless connectivity (more than 50 billion connected devices are expect
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