Simplified MMSE Precoding Design in Interference Two-Way MIMO Relay Systems

Nguyen, Khoa Xuan; Rong, Yue; Nordholm, Sven

doi:10.1109/lsp.2015.2513482

Cited by 9 publications

(9 citation statements)

References 20 publications

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“…Equating ∇ W H k (tr (E k )) = 0 yields the linear MMSE receive filter given by (11) where (·) −1 indicates the inversion operation of a matrix. Then for given source and receiver matrices {B k } and {W k }, the relay precoding matrix F optimization problem can be formulated as…”

Section: Iterative Joint Transceiver Optimizationmentioning

confidence: 99%

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Joint source and relay optimization for interference MIMO relay networks

Khandaker¹,

Wong²

2017

EURASIP J. Adv. Signal Process.

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This paper considers multiple-input multiple-output (MIMO) relay communication in multi-cellular (interference) systems in which MIMO source-destination pairs communicate simultaneously. It is assumed that due to severe attenuation and/or shadowing effects, communication links can be established only with the aid of a relay node. The aim is to minimize the maximal mean-square-error (MSE) among all the receiving nodes under constrained source and relay transmit powers. Both one-and two-way amplify-and-forward (AF) relaying mechanisms are considered. Since the exactly optimal solution for this practically appealing problem is intractable, we first propose optimizing the source, relay, and receiver matrices in an alternating fashion. Then we contrive a simplified semidefinite programming (SDP) solution based on the error covariance matrix decomposition technique, avoiding the high complexity of the iterative process. Numerical results reveal the effectiveness of the proposed schemes.

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Section: Iterative Joint Transceiver Optimizationmentioning

confidence: 99%

“…Note that the optimal receiver matrices {W k } can be obtained as in (11). Interestingly, the source and relay optimization variables {B k } andT are separable both in the objective function as well as in the constraints in problem (25).…”

Section: Proposition 1 In the Practically Reasonably High Snr Regimementioning

confidence: 99%

Joint source and relay optimization for interference MIMO relay networks

Khandaker¹,

Wong²

2017

EURASIP J. Adv. Signal Process.

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“…For similar reasons, mean square error (MSE) has been popularly used for beamforming design in two-way relay systems in the literature such as [13]- [18].…”

Section: Mmse Based Beamforming Designmentioning

confidence: 99%

Beamforming Design for Full-Duplex Two-Way Amplify-and-Forward MIMO Relay

Shim

Choi

Park

2016

IEEE Trans. Wireless Commun.

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We consider the full-duplex (FD) two-way amplify-and-forward relay system with imperfect cancelation of loopback self-interference (SI) and investigate joint design of relay and receive beamforming for minimizing the mean square error under a relay transmit power constraint. Due to loopback channel estimation error and limitation of analog-to-digital converter, the loopback SI cannot be completely canceled. Multiple antennas at the relay can help loopback SI suppression but beamforming is required to balance between the residual SI suppression and the desired signal transmission. Moreover, the relay beamforming matrix should be updated every time slot because the residual SI in the previous time slot is amplified by the current beamforming matrix and added to the received signals from the two sources in the current time slot. We derive the optimally balanced relay beamforming and receive beamforming matrices in closed form based on minimum mean square error, taking into account the propagation of the residual loopback SI from the first to the current time slot. We also propose beamforming design using only the channels of the m latest time slots, not from the first time slot. Based on our numerical results, we also identify when FD is beneficial and propose selection between FD and half-duplex according to signal-to-noise ratio and interference-to-noise ratio.

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“…Various designs have been conceived for canceling the MUI by using a multiple-input multiple output (MIMO) relay and for optimizing diverse metrics, such as the sum-rate, and the rate of the user having the weakest signal-to-interference-plus-noise ratio (SINR) [5]- [9]. The authors of [5], [6] constructed precoders for the relay based on the zero-forcing and the linear minimum mean squared error criteria respectively, for canceling both the SI and the MUI experienced by the users. Gunduz et al [7] characterized the sum-rate of the multi-user Gaussian TWR while Fang et al [8] designed a relay precoder for maximizing the SINR of the weakest user.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Quantized MRC-MRT Precoder For FDD Massive MIMO Two-Way AF Relaying

Dutta

Budhiraja

Koilpillai

et al. 2019

IEEE Trans. Commun.

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The maturing massive multiple-input multipleoutput (MIMO) literature has provided asymptotic limits for the rate and energy efficiency (EE) of maximal ratio combining /maximal ratio transmission (MRC-MRT) relaying on two-way relays (TWR) using the amplify-and-forward (AF) principle. Most of these studies consider time division duplexing, and a fixed number of users. To fill the gap in the literature, we analyze the MRC-MRT precoder performance of a N-antenna AF massive MIMO TWR, which operates in frequency division duplex mode to enable two-way communication between 2M = ⌊N α ⌋ singleantenna users, with α ∈ [0, 1), divided equally in two groups of M users. We assume that the relay has realistic imperfect uplink channel state information (CSI), and that quantized downlink CSI is fed back by the users relying on B ≥ 1 bits peruser per relay antenna. We prove that for such a system with α ∈ [0, 1), the MRC-MRT precoder asymptotically cancels the multiuser interference (MUI) when the supremum and infimum of large scale fading parameters is strictly non-zero and finite, respectively. Furthermore, its per-user pairwise error probability (PEP) converges to that of an equivalent AWGN channel as both N and the number of users 2M = ⌊N α ⌋ tend to infinity, with a relay power scaling of Pr = 2M Er N and Er being a constant. We also derive upper bounds for both the per-user rate and EE. We analytically show that the quantized MRC-MRT precoder requires as few as B = 2 bits to yield a BER, EE, and per-user rate close to the respective unquantized counterparts. Finally, we show that the analysis developed herein to derive a bound on α for MUI cancellation is applicable both to Gaussian as well as to any arbitrary non-Gaussian complex channels.

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Simplified MMSE Precoding Design in Interference Two-Way MIMO Relay Systems

Cited by 9 publications

References 20 publications

Joint source and relay optimization for interference MIMO relay networks

Joint source and relay optimization for interference MIMO relay networks

Beamforming Design for Full-Duplex Two-Way Amplify-and-Forward MIMO Relay

Analysis of Quantized MRC-MRT Precoder For FDD Massive MIMO Two-Way AF Relaying

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