Joint MMSE designs for analog network coding and different MIMO relaying schemes: A unified approach and performance benchmarks

Li, Jialing; Lu, Enoch; Lu, I‐Tai

doi:10.1016/j.phycom.2012.02.003

Cited by 2 publications

(6 citation statements)

References 21 publications

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“…After the above iteration is finished, remove any all zero columns from F 1 and F 2 . This does not change I E1 and I E2 in (10). However, it's needed so that (8) can be simplified to (10).…”

Section: The Iterative Proceduresmentioning

confidence: 99%

“…This does not change I E1 and I E2 in (10). However, it's needed so that (8) can be simplified to (10). Also, scale T to satisfy the relay power constraint if the iteration terminated before convergence.…”

Section: The Iterative Proceduresmentioning

confidence: 99%

“…Analog network coding (e.g., [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]), also known as twoway amplify-and-forward relaying, is a bi-directional relaying technique. Its data transmission takes half the time of conventional bi-directional relaying.…”

Section: Introductionmentioning

confidence: 99%

“…However, the design of these five matrices is not trivial. Some papers try to optimize according to some criteria (e.g., [8][9][10][11]) while others seek to propose low-complexity heuristics (e.g., [12,13]). Since the optimization problems are highly nonlinear, the solutions have only been derived numerically (or approximately) and are innately suboptimum.…”

Section: Introductionmentioning

confidence: 99%

“…Both [6,7] are different from the GIA in that they are both based on the assumption that source precoders are given beforehand. Like the GIA, the studies [9,10] are also for the design of the precoders, decoders, and relay processor. However, its criterion is minimum mean squared error (MMSE).…”

Section: Introductionmentioning

confidence: 99%

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Decentralized practical design and centralized benchmark for analog network coding

You

2013

EURASIP J. Adv. Signal Process.

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This article proposes both centralized and decentralized design schemes for an analog network coding multipleinput multiple-output system with a relay node between two end nodes. The proposed centralized scheme is called the generalized iterative approach (GIA). It jointly designs the precoders and decoders at the two end nodes, and the processor at the relay to maximize the sum mutual information. Numerical results for the per-node power constraint show the convergence behavior of the GIA and give a performance benchmark for the analog network coding scheme. The proposed decentralized scheme is a practical joint transceiver and signaling design scheme. The keys to its low signaling load are time-division duplex and a symmetric relay processing matrix. The proposed signaling protocol enables the needed information, including channel state information (CSI), to be available at each node. With the needed CSI, a novel symmetric processor design at the relay is developed to maximize an approximate sum mutual information formula (to reduce the signaling loading, the precoders at both end nodes and the noise propagated from the relay are not considered). Employing singular value decomposition transceivers at the two end nodes, it is remarkable that the proposed decentralized approach performs almost as well as the centralized GIA design. It is concluded that the proposed decentralized scheme is a feasible way to implement analog network coding systems.

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Section: The Iterative Proceduresmentioning

confidence: 99%

Section: The Iterative Proceduresmentioning

confidence: 99%