Compress-and-forward strategy for relay channel with causal and non-causal channel state information

Abstract

The discrete memoryless state-dependent relay channel (SD-RC) is considered in this study. Two main cases are investigated: SD-RC with non-causal channel state information (CSI) and SD-RC with causal CSI. In each case, the SD-RC with partial CSI at the source and the relay is considered. As special cases it includes three different situations in which perfect CSI is available: (i) only at the source, (ii) only at the relay and (iii) both at the source and the relay. For the non-causal situation, the authors establish lower bound on capacity (achievable rate) of the SD-RC, using Gel'fand-Pinsker coding at the nodes informed of CSI and compress-andforward (CF) strategy at the relay. Using the Shannon's strategy and CF relaying, the authors derive lower bound on capacity of SD-RC in the causal case. Furthermore, in order to compare their derived bounds with the previously obtained results, which are based on the decode-and-forward (DF) strategy, the authors consider general Gaussian relay channel (RC) with additive independent and identically distributed Gaussian state and noise, and obtain lower bounds on capacity for the cases in which perfect CSI is available noncausally at the source or at the relay. They also present cases in which their lower bounds outperform DFbased bounds, and can achieve rates close to the upper bound. For causal case, a numerical example of the binary fading Gaussian RC with additive noise is provided.

The capacity of a class of state-dependent relay channel with orthogonal components and side information at the source and the relay

“…The state-dependent relay channels were studied in [16][17][18][19][20][21]. Zaidi et al [16] studied the relay channel with non-causal channel state information known to only the relay.…”

“…A similar orthogonal relay channel that was corrupted by an interference which was known noncausally to the source was considered in [20], in which several transmission strategies were proposed, assuming the interference had structure. Akhbari et al [21] considered a state-dependent relay channel in three different cases: only the relay or only the source or both the source and the relay knew the channel state information non-causally. Lower bounds of the capacity were established based on using GP coding and compress-andforward (CF) relaying for the three cases.…”

Impact of partial relay selection on the capacity of communications systems with outdated CSI and adaptive transmission techniques

“…The type of relaying modes can be largely classified as amplify-and-forward (AF) and decode-and-forward (DF), where in the former, relay directly retransmits a linearly amplified version of the received signal to the destination without any modification to the signal, but in the latter, relay demodulates and possibly re-modulates the received information before forward it [8,9]. Besides AF and DF, some other wellknown relaying mode, such as compress-and-forward (CF), has also been studied considerably to obtain a performance gain by performing signal compression at the relays [10].…”

State-Dependent Relay Channel: Achievable Rate and Capacity of a Semideterministic Class

“…In this paper, we study the relay channel with state, which consists of a sender (i.e., source), a relay, and a destination. We assume that the state is determined by a random parameter, and that noncausal knowledge of the state is partially available at the nodes, cf., [7]- [9] for related work. We present a general lower bound on the achievable rates using the noisy network coding (NNC) scheme in [10] and the Gelfand-Pinsker multicoding scheme [11].…”

“…We present a general lower bound on the achievable rates using the noisy network coding (NNC) scheme in [10] and the Gelfand-Pinsker multicoding scheme [11]. Although this achievable rate coincides with that in [9], it provides an alternative characterization that leads to a nontrivial optimality result. We then introduce the special class of state-decoupled relay channels and show that the general lower bound is tight for a semideterministic subclass of these channels.…”