2015
DOI: 10.1109/tsp.2014.2376885
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Joint Beamforming Optimization and Power Control for Full-Duplex MIMO Two-Way Relay Channel

Abstract: Abstract-In this paper we explore the use of full-duplex radio to improve the spectrum efficiency in a two-way relay channel where two sources exchange information through an multi-antenna relay, and all nodes work in the full-duplex mode. The full-duplex operation can reduce the overall communication to only one phase but suffers from the self-interference. Instead of purely suppressing the self-interference, we aim to maximize the end-to-end performance by jointly optimizing the beamforming matrix at the rel… Show more

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Cited by 157 publications
(102 citation statements)
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“…(3.471.9)], which upon substituting I 1 into (45), results in (25), this finishes the proof. 11 Alternatively, one could choose w T as w T = (27), that finishes the proof.…”
Section: Appendix C Proof Of Propositionmentioning
confidence: 87%
“…(3.471.9)], which upon substituting I 1 into (45), results in (25), this finishes the proof. 11 Alternatively, one could choose w T as w T = (27), that finishes the proof.…”
Section: Appendix C Proof Of Propositionmentioning
confidence: 87%
“…Our idea is to optimize a portion of variables when the others are fixed and then search all the potential results to produce the optimal solution [16], [17]. More specifically, in the first step, we try to find the solutions of W and Q x for fixed P 1 , P 2 and ρ values.…”
Section: Iterative Optimization Algorithmmentioning
confidence: 99%
“…For simplicity, we follow [27] and assume that the full channel state information is known perfectly at the relay. Without loss of generality, we hereafter consider a normalized time duration of each transmission block, i.e., T = 1.…”
Section: Relaymentioning
confidence: 99%
“…It is observed that the receive beamforming vector w r is only involved in the terms which has the same form as function (33) in [27], and can be solved similarly through D-C programming [26] to find an optimal solution. Specifically, we can express F (W t ) as a difference of two concave functions f (W t ) and g (W t ), i.e., We then approximate g (W t ) by a linear function.…”
mentioning
confidence: 99%