Bi-directional differential beamforming for multi-antenna relaying

Schad, Adrian; Alabed, Samer; Degenhardt, Holger; Pesavento, Marius

doi:10.1109/icassp.2015.7178498

Cited by 19 publications

(48 citation statements)

References 34 publications

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“…. , No rand (10) Note that generating more instances of a random vector e k will increase the probability to have one of them as close as possible to the optimal one. By doing this, the overall BER performance will improve.…”

Section: Step 2: Generating Random Vectormentioning

confidence: 99%

“…. , N o rand the soft decoded randomized symbol vector x k generating according to (10) to hard decoded symbol vectorx k by finding the nearest constellation point for each soft decoded symbol as shown in Figure 2. Note that this is a symbol by symbol processing step performed using the round operation with almost no additional computational complexity.…”

Section: Step 3: Hard Decodingmentioning

confidence: 99%

“…In the last decade, cooperative and multiple-input multiple-output (MIMO) techniques have been extensively studied as their improvements in performance do not require additional power or frequency spectrum [1][2][3][4][5][6][7][8][9][10][11][12][13]. In this work, the performance of existing linear and nonlinear decoders [2,[14][15][16][17][18][19][20] for MIMO systems is compared with the newly proposed decoder that is particularly suitable for implementation on software-defined-radio architectures.…”

Section: Introductionmentioning

confidence: 99%

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A computationally efficient detector for MIMO systems

Alabed

2019

IJECE

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<p>In this work, a newly designed multiple-input multiple-output (MIMO) detector for implementation on software-defined-radio platforms is proposed and its performance and complexity are studied. In particular, we are interested in proposing and evaluating a MIMO detector that provides the optimal trade-off between the decoding complexity and bit error rate (BER) performance as compared to the state of the art detectors. The proposed MIMO decoding technique appears to find the optimal compromise between competing interests encountered in the implementation of advanced MIMO detectors in practical hardware systems where it i) exhibits deterministic decoding complexity, i.e., deterministic latency, ii) enjoys a good complexity–performance trade-off, i.e., it keeps the complexity considerably lower than that of the maximum likelihood detectors with almost optimal performance, iii) allows fully parameterizable performance to complexity trade-off where the performance (or complexity) of the MIMO detector can be adaptively adjusted without the requirement of changing the implementation, iv) enjoys simple implementation and fully supports parallel processing, and v) allows simple and efficient extension to soft-bit output generation for support of turbo decoding. From the simulation results, the proposed MIMO decoding technique shows a substantially improved complexity–performance trade-off as compared to the state of the art techniques.</p>

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Section: Step 2: Generating Random Vectormentioning

confidence: 99%

Section: Step 3: Hard Decodingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A computationally efficient detector for MIMO systems

Alabed

2019

IJECE

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“…Differential modulation has recently received considerable interest as it offers diversity and coding gain without the need for channel estimation [1][2][3][4][5][6][7][8]. Relaying techniques for wireless communication systems have been studied extensively in the last decade [9][10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Distributed differential beamforming and power allocation for cooperative communication networks

Alabed

Maaz

Al-Rabayah

2020

IJECE

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Many coherent cooperative diversity techniques for wireless relay networks have recently been suggested to improve the overall system performance in terms of the achievable data rate or bit error rate (BER) with low decoding complexity and delay. However, these techniques require channel state information (CSI) at the transmitter side, at the receiver side, or at both sides. Therefore, due to the overhead associated with estimating CSI, distributed differential space-time coding techniques have been suggested to overcome this overhead by detecting the information symbols without requiring any (CSI) at any transmitting or receiving antenna. However, the latter techniques suffer from low performance in terms of BER as well as high latency and decoding complexity. In this paper, a distributed differential beamforming technique with power allocation is proposed to overcome all drawbacks associated with the later techniques without needing CSI at any antenna and to be used for cooperative communication networks. We prove through our analytical and simulation results that the proposed technique outperforms the state-of-the-art techniques in terms of BER with comparably low decoding complexity and latency.

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“…To mitigate the difficulties involved in CSI estimation in the TWRN, several non-coherent and differential relaying schemes have been proposed in the literature [11]- [15]. For TWRN with a single-antenna relay node, the authors proposed differential transmission schemes with amplify-and-forward and Decode-and-Forward (DF) protocols in [11].…”

Section: Introductionmentioning

confidence: 99%

Differential Network Coded Transmission for Two-Way Relay Networks with Large Antenna Array

Fang¹,

Shao²,

Wen³

et al. 2016

JCM

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This paper considers a two-way relay network (TWRN) with two sources and one relay node, where each source is equipped with a single antenna, while the relay node is equipped with a large number of antennas. We propose two low-complexity physical-layer differential network coding schemes for such TWRNs, namely, Superimposition Coding based Differential Beamforming (SC-DBF) and Decode-and-Forward based Differential Beamforming (DF-DBF). In the proposed schemes, no Channel State Information (CSI) is required at each source node for signal detection. It is shown that as the number of relay antennas becomes large, the received signal at each source node includes the desired signal only, and simple linear detector can be used to exploit the benefits of massive array in both schemes. Numerical results are presented to demonstrate the Bit-to-Error Rate (BER) performance of the proposed SC-DBF and DF-DBF schemes.

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Bi-directional differential beamforming for multi-antenna relaying

Cited by 19 publications

References 34 publications

A computationally efficient detector for MIMO systems

A computationally efficient detector for MIMO systems

Distributed differential beamforming and power allocation for cooperative communication networks

Differential Network Coded Transmission for Two-Way Relay Networks with Large Antenna Array

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