Channel estimation for amplify-and-forward relaying: cascaded against disintegrated estimators

Abstract

The authors investigate the performance of amplify-and-forward relaying with two different pilotsymbol-assisted channel estimation methods. In the first estimation method, the cascaded channel consisting of source-to-relay and relay-to-destination links is estimated at the destination terminal. No channel estimator is required at the relay terminal. In the second estimation method, the estimation of cascaded channel is disintegrated into separate estimations of source-to-relay and relay-to-destination links which are carried out at the relay and the destination terminals, respectively. The latter method involves feed-forwarding a quantised version of the source-to-relay channel estimate to the destination terminal. Through the derivation of mean squared error (MSE) diversity gain analysis and Monte-Carlo simulations, the authors investigate the performance of amplify-and-forward relaying with these channel estimation methods. Our results demonstrate that full diversity can be achieved in the presence of channel estimation. The authors further show that cascaded channel estimator outperforms its competitor with a small number of quantisation bits. As the number of employed quantisation bits increase, disintegrated channel estimator approaches to its competitor eventually outperforming it.

Optimal Bit and Power Loading for Amplify-and-Forward Cooperative OFDM Systems

“…For OBL and EBPL, mid-locations between source and destination become more favourable. For near-to-destination and near-to-source locations, they exhibit identical channel statistical properties [29] and therefore yield symmetric performance around 0 dB location. …”

“…CSI for the direct link (i.e., S→D) and relaying link (i.e., S→R and R→D) is also used at the destination for detection process. For the estimation of relaying path, we adopt the socalled disintegrated channel estimation (D-CE) approach [29] in which S→R and R→D channels are estimated separately. In this approach, the relay node is equipped with a channel estimator and feed-forwards the S→R channel estimate to the destination terminal as well as feedbacks it to the source.…”

Pilot-Based Channel Estimation for AF Relaying Using Energy Harvesting

“…Several works have been conducted on channel estimation for relaying, which mainly focused on the minimum mean squared error (MMSE) estimation and the cascaded channel estimation, such as in [9], [10] and [12]. In [11], a least squares estimator was also proposed.…”

Exploiting a priori information for iterative channel estimation in block-fading amplify-and-forward cooperative networks

“…It has been proposed (e.g., the linear minimum mean-square *Correspondence: nico.aerts@telin.ugent.be TELIN, UGent, Gent 9000, Belgium error (LMMSE) cascaded channel estimation from [4,5]) that the destination estimates the overall channel gain but takes the overall noise variance equal to the variance obtained by averaging over the statistic of the relaydestination channel, whereas in [6] the relay-destination channel gain is estimated separately (and the noise variance computed accordingly) at the expense of a more sophisticated relay (that adds pilot symbols of its own). The LMMSE disintegrated estimation from [5] involves the estimation of the source-relay channel at the relay (which significantly increases relay complexity) and the relay-destination channel at the destination, whereas [7] considers maximum-likelihood (ML) estimation of both these channels at the destination. In [8], ML estimation of the overall channel gain and noise variance is performed at the destination; these results are extended in [9] to the case of a multi-antenna destination.…”

“…In this contribution, we present two pilot-based and two space-alternating generalized expectation-maximization (SAGE) [10] algorithms for estimating at the destination both the overall channel gain and (unlike the cascaded channel estimation from [5]) the overall noise variance. In contrast with [6][7][8][9], the proposed algorithms also take a priori channel knowledge into account.…”