EM based channel estimation in an amplify-and-forward relaying network

Cooperative communication offers a way to obtain spatial diversity in a wireless network without increasing hardware demands. The different cooperation protocols proposed in the literature [1] are often studied under the assumption that all channel state information is available at the destination. In a practical scenario, channel estimates need to be derived from the broadcasted signals. In this paper, we study the Amplify-and-Forward protocol and use the expectation-maximization (EM) algorithm to obtain the channel estimates in an iterative way. Our results show that the performance of the system that knows the channels can be approached at the cost of an increased computational complexity. In case a small constellation is used, a low complexity approximation is proposed with a similar performance

EM based channel estimation in an amplify-and-forward relaying network

Cooperative communication offers a way to obtain spatial diversity in a wireless network without increasing hardware demands. The different cooperation protocols proposed in the literature [1] are often studied under the assumption that all channel state information is available at the destination. In a practical scenario, channel estimates need to be derived from the broadcasted signals. In this paper, we study the Amplify-and-Forward protocol and use the expectation-maximization (EM) algorithm to obtain the channel estimates in an iterative way. Our results show that the performance of the system that knows the channels can be approached at the cost of an increased computational complexity. In case a small constellation is used, a low complexity approximation is proposed with a similar performance

Relay Switching Aided Turbo Coded Hybrid-ARQ for Correlated Fading Channel

Hybrid-Automatic-Repeat-reQuest (HARQ) has become an indispensable technique in reliable communications systems. However, its performance is inevitably affected by the channel’s fading correlation. In this paper, we proposed a novel relay-switching aided HARQ scheme in order to mitigate the detrimental effects of correlated fading without unduly increasing the system’s complexity and delay. Our results show that the proposed relay-switching regime operates efficiently in correlated channels, hence significantly reduces the error floor of turbo-coded HARQ. Additionally, a HARQ scheme using Segment Selective Repeat (SSR) is incorporated in the relay-switching scheme for achieving further improvements. Quantitatively, the proposed relay-switching aided turbo-coded HARQ scheme using SSR may achieve an approximately 2 dB gain, compared to the conventional amplify-and-forward aided turbo coded HARQ arrangement using Chase Combining. Index Terms - Relay switching, correlated fading channel, Hybrid-ARQ, turbo codes, chase combining, incremental redundancy, selective segment repeat

SAGE-based estimation algorithms for time-varying channels in amplify-and-forward cooperative networks

Cooperative communication is a technique that achieves spatial diversity by exploiting the presence of other nodes in the network. Most analyses of such networks are conducted under the simplifying assumption of perfect channel knowledge. In this paper we focus on the popular Amplify-and-forward (AF) cooperative protocol. We propose several SAGE-based iterative algorithms with different complexities for estimating the channel gain and noise variance in the case of time-varying channels. Computer simulations are provided to evaluate their performance over Rice-fading channels. We point out a low-complexity estimation algorithm yielding an error performance that (for Rayleigh fading) is only about 0.5 dB worse than in the case of perfect estimation, while outperforming a pilot-based estimation algorithm by about 1.5 dB

Maximum-likelihood channel estimation in block fading amplify-and-forward relaying networks

Several diversity techniques have been proposed to counteract the effect of fading on the error performance of wireless networks. A recent and promising technique, which achieves spatial diversity without increased hardware demands, is cooperative communication, involving other terminals in the network that relay the information broadcasted by the source terminal to the destination terminal. In literature several cooperative protocols have been studied under the simplifying assumption that all channel state information is available at the destination. In this paper, we use the space-alternating generalized expectation-maximization (SAGE) algorithm to perform codeaided iterative channel estimation from the broadcasted signals in an Amplify-and-Forward protocol, and investigate the resulting error performance

Simultaneous Estimation of Multi-Relay MIMO Channels

This paper addresses training-based channel estimation in distributed amplify-and-forward (AF) multi-input multi-output (MIMO) multi-relay networks. To reduce channel estimation overhead and delay, a training algorithm that allows for simultaneous estimation of the entire MIMO cooperative network’s channel parameters at the destination node is proposed. The exact Cram´er- Rao lower bound (CRLB) for the problem is presented in closedform. Channel estimators that are capable of estimating the overall source-relay-destination channel parameters at the destination are also derived. Numerical results show that while reducing delay, the proposed channel estimators are close to the derived CRLB over a wide range of signal-to-noise ratio values and outperform existing channel estimation methods. Finally, extensive simulations demonstrate that the proposed training method and channel estimators can be effectively deployed in combination with cooperative optimization algorithms to significantly enhance the performance of AF relaying MIMO systems in terms of average-bit-error-rate