Coded Cooperative Data Exchange in Multihop Networks

Courtade, Thomas A.; Wesel, Richard D.

doi:10.1109/tit.2013.2290993

Cited by 64 publications

(141 citation statements)

References 30 publications

(52 reference statements)

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“…However, using such strong Forward error correction channel code, which is Partial Unit Memory Turbo Code (PUMTC) results to minimize the losses in the BER to a very acceptable lever, in fact, in Decode-and-Forward (DF) BS, the BER can be regarded as minimum. Simulation results, for both Amplify-and-Forward (AF) and DF BS schemes using PUMTC based on (8,4,3,8) component codes, confirm that using PUMTC mitigates the problem of noise aggregation resulting from applying NC in the proposed schemes. …”

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confidence: 71%

“…For rate 1/3 PUMTCs based on (8,4,3,8) PUM component codes, a pseudo-random interleaver of size 1000 bits is used. These PUM code designs and turbo code set-ups are described in [15] [16].…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In [8], data exchange scenario is investigated for fully connected network, via a polynomial-time algorithm with a proposed transmission strategy, unlike the work proposed in this paper where a deterministic XORing combination strategy using NC is proposed. In [9], a Dynamic Source Routing (DSR) is proposed for multi-hops mobile Ad hoc networks, where DSR technique using NC is applied to reduce the number of transmissions.…”

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confidence: 99%

“…On the other hand, DF is not recommended for real-time application because of the time delay in the decoding and re-encoding, but it has such high BER performance. A practical system designs based on a rate 1/3 PUMTC with two (8,4,3,8) PUM component codes, is provided.…”

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Data Combination over Physical Layer Using Network Coding with PUM Turbo Codes

Attar¹

2017

JCC

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The Base Station (BS) or access point is the building block of wireless networks, so, we propose exploiting it together with the Network Coding (NC) principle. NC suffers from the complexity of the decoding processes, i.e., complicated Jordan Gaussian Elimination (JGE) processes. So, this paper proposes a deterministic NC algorithm to reduce the number of sequential network decoding steps, and hence minimizing the complexity of JGE process resulting to better time delay and processing time. We propose an algorithm that combines higher number of the transmitted packets resulting to better data-rate but worse Bet Error Rate (BER). However, using such strong Forward error correction channel code, which is Partial Unit Memory Turbo Code (PUMTC) results to minimize the losses in the BER to a very acceptable lever, in fact, in Decode-and-Forward (DF) BS, the BER can be regarded as minimum. Simulation results, for both Amplify-and-Forward (AF) and DF BS schemes using PUMTC based on (8,4,3,8) component codes, confirm that using PUMTC mitigates the problem of noise aggregation resulting from applying NC in the proposed schemes.

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confidence: 71%

Section: Simulation Resultsmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Data Combination over Physical Layer Using Network Coding with PUM Turbo Codes

Attar¹

2017

JCC

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“…It has been recently shown that a deterministic algorithm based on conditional basis construction [1] can solve this optimization problem with lower complexity. The CDE problem has also been extended in heterogeneous directions, including CDE for arbitrarily connected network [7], [8], successive omniscience and priority [9], [10], and optimization on weighted cost or fairness rate allocations [6], [11], [12].…”

Section: A Related Workmentioning

confidence: 99%

Cooperative data exchange with weighted cost based on d-basis construction

Shah

Gastpar

2017

2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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Abstract-We consider the cooperative data exchange problem, in which nodes are fully connected with each other. Each node initially only has a subset of the K packets making up a file and wants to recover the whole file. Node i can make a broadcast transmission, which incurs cost wi and is received by all other nodes. The goal is to minimize the total cost of transmissions that all nodes have to send, which is also called weighted cost. Following the same idea of our previous work [1] which provided a method based on dBasis construction to solve cooperative data exchange problem without weighted cost, we present a modified method to solve cooperative data exchange problem with weighted cost. We present a polynomial-time deterministic algorithm to compute the minimum weighted cost and determine the rate vector and the packets that should be used to generate each transmission. By leveraging the connection to Maximum Distance Separable codes, the coefficients of linear combinations of the optimal coding scheme can be efficiently generated. Our algorithm has significantly lower complexity than the state of the art. In particular, we prove that the minimum weighted cost function is a convex function of the total number of transmissions for integer rate cases.

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