Joint maximum likelihood detection and link selection for cooperative MIMO relay systems

Abstract

In this study, the authors propose a cross layer design strategy that consists of a cooperative maximum likelihood detector operating in conjunction with link selection for cooperative multiple-input multiple-output relay networks. The system considered is a two phase relaying model, with amplify-and forward relays. The model considers the effect of relay placement and of large scale shadowing. The authors develop a cooperative maximum likelihood detector for an arbitrary number of relays, and link selection schemes are devised for two scenarios relating to the available knowledge at the destination node, which considers relay combination, with complexity analysis. The authors also propose a cooperative list sphere decoder that processes soft information and implements an iterative detection and decoding scheme. The results of simulations of the systems are presented, with comparisons to system models used in previous literature, and show how the cooperative detector and the proposed link selection schemes affect the bit error rate performance at the destination node, for both the hard decision non-iterative case, and the soft information iterative processing case.

Distributed Robust Beamforming Based on Low-Rank and Cross-Correlation Techniques: Design and Analysis

“…The channel matrices F and g are modeled as Rayleigh distributed random variables and we also consider distancebased large-scale channel propagation effects such as path loss and shadowing. An exponential based path loss model is described by [35]…”

“…where γ m is the distance-based path loss, L is the known path loss at the destination, d m is the distance of interest relative to the destination and ρ is the path loss exponent, which can vary due to different environments and is typically set within 2 to 5, with a lower value representing a clear and uncluttered environment, which has a slow attenuation, and a higher value describing a cluttered and highly attenuating environment. Shadow fading can be described as a random variable with a probability distribution described by [35] β m = 10 ( σs η 10 ) ,…”

“…where β is the shadowing parameter, η ∼ N (0, 1) means η is drawn from a Gaussian distribution with zero mean and unit variance and σ s is the shadowing spread in dB. The shadowing spread reflects the severity of the long-term attenuation caused by shadowing, and is typically given between 0dB to 9dB [35]. Without losing generality, for simplicity we assume all relays share the same value of ρ and σ s , and that the signal sources are close enough so that they can be treated as a source pool.…”

Cloud-Aided Max-Link Relay Selection for Two-Way Cooperative Multi-Antenna Systems

“…Considering imperfect CSI, the estimated channel matrixĤ is assumed, instead of H in (2), (5) and (8) . Thus, the variance of the H e coefficients is given by σ 2 e = βE −α (β ≥ 0), in the case of H S,R k or H Rj,D , and σ 2 e = β(2E) −α , in the case of H S,D .…”

“…I N wireless networks, signal fading caused by multipath propagation is a channel propagation phenomenon that can be mitigated through the use of cooperative diversity [1], [2], [3]. In cooperative communications with multiple relays, where a number of relays help a source to transmit data packets to a destination, by receiving, decoding and forwarding these packets, relay selection schemes are key because of their high performance [4], [5], [6]. As cooperative communication can improve the throughput and extend the coverage of wireless communications systems, the task of relay selection serves as a building block to realize it.…”