A Cyclic Shift Relaying Scheme for Asynchronous Two-way Relay Networks

Fang, Zhaoxi; Liang, Feng; Zhang, Shaozhong; Peng, Tao

doi:10.1007/s11277-012-0975-x

Cited by 9 publications

(4 citation statements)

References 17 publications

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“…In [18], the authors consider an asynchronous bidirectional relay network, where a single multi-antenna relay enables a two-way information exchange between two transceivers, and devise a channel and timing offset estimation method to re-synchronize the relays. The study in [19] considers a bi-directional relay network, with multiple single-antenna relays. In the communication scheme of [19], the transceivers insert cyclic prefix (CP) in their transmit signals while each relay removes the CP from its received signal, circularly shifts the residual signal, inserts the CP again, and retransmits the so-obtained signal.…”

Section: Introductionmentioning

confidence: 99%

“…The study in [19] considers a bi-directional relay network, with multiple single-antenna relays. In the communication scheme of [19], the transceivers insert cyclic prefix (CP) in their transmit signals while each relay removes the CP from its received signal, circularly shifts the residual signal, inserts the CP again, and retransmits the so-obtained signal. The transceivers employ linear post-channel equalization schemes (such as zero forcing (ZF) and MMSE receivers) at their receiver front-ends.…”

Section: Introductionmentioning

confidence: 99%

“…The transceivers employ linear post-channel equalization schemes (such as zero forcing (ZF) and MMSE receivers) at their receiver front-ends. For such a communication scheme, the authors of [19] study the bit error rate (BER) performance and present a BER-optimal power allocation method. In [20], the authors consider a bi-directional DF relay network and present post-channel equalization schemes, such as MMSE and MMSE decision feedback equalizers for the case when multiple frequency offsets are present at the relays.…”

Section: Introductionmentioning

confidence: 99%

“…The goal in [18] is to develop a channel and timing offset estimation method that can be used to re-synchronization the relays, whereas we herein do not re-synchronize the relays but employ post-channel equalization to suppress the ISI at the two transceivers induced by the relays. Unlike [19], which relies on circularly shifting (cyclic delay) of the CP-free signal at the relays, we assume AF relaying without any cyclic delay for the sake of relay simplicity. The relaying scheme considered in [20] relies on a decode-and-forward protocol while the relaying scheme in this paper is an AF technique.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Proof of the Equivalency of MSE-Constrained and Rate-Constrained Power Optimization Approaches to Distributed Bi-Directional Beamforming

Rahimi

Shahbazpanahi

Ottersten

2020

IEEE Trans. on Signal and Inf. Process. over Networks

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Considered in this article is an asynchronous singlecarrier two-way relay network, where two transceivers aim to communicate through a set of amplify-and-forward (AF) relays. This network is asynchronous in the sense that the signal transmitted by any of the two transceivers arrives the other transceiver through different relaying paths, with possibly different propagation delays, thereby materializing a multipath channel. At sufficiently high data rates, this multi-path end-to-end channel causes inter-symbol-interference (ISI) in the received signals. Considering such a network, this paper presents two contributions. The first contribution is the rigorous characterization of the region of the mean-squared errors (MSEs) of the symbol estimates at the two transceivers under a total power budget, and when linear block post-channel equalization is used at the receiver front-end of the two transceivers. The importance of this MSE region characterization resides in the fact that knowing this region allows for characterization the region of un-coded probabilities of error at the two transceivers. Also, this MSE region characterization paves the way towards presenting the second contribution in this paper. Indeed, in the second contribution, this article relies on this MSE region characterization to rigorously prove that an MSE-constrained total power minimization approach and a rate-constrained total power minimization approach to design transceiver power allocation and distributed beamforming are equivalent, if the MSE thresholds in the former approach and the rate thresholds in the latter approach are properly chosen. The equivalence of these two approaches implies that the un-coded MSE performance of the network can be inferred from the rate-constrained problem, and conversely, the coded rate performance of the network can be inferred from the MSE-constrained total power minimization problem.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%