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Compute-and-Forward: Optimization Over Multisource–Multirelay Networks

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Compute-and-Forward: Optimization Over Multisource–Multirelay Networks


In this paper, we investigate a multisource multicast network with the help of an arbitrary number of relays, where it is assumed that no direct link is on the market at every S-D pair. The aim is to find the elemental limit on the maximal common multicast throughput of all source nodes if resource allocations are out there. A transmission protocol employing the relaying strategy, i.e., compute-and-forward (CPF), is proposed. We have a tendency to also change the methods within the literature to obtain the integer network-constructed coefficient matrix (i.e., a naive method, a local optimal method, and a international optimal technique) to fit the overall topology with an arbitrary variety of relays. 3 transmission situations are addressed. The primary situation is delay-stringent transmission, where each message must be delivered inside one slot. The second situation is delay-tolerant transmission where no delay constraint is imposed. The associated optimization issues to maximize the short- and long-term common multicast throughputs are formulated and solved, and also the optimal allocation of power and time slots are presented. The third case (a general -slot-delay-tolerant situation) is also mentioned, and a suboptimal algorithm is presented. Performance comparisons show that the CPF strategy outperforms conventional decode-and-forward (DF) strategy. It's additionally shown within the simulation that with additional relays, the CPF strategy performs even higher because of the increased diversity. Finally, by simulation, it's observed that, with CPF, the -slot-delay-constraint case will perform close to that of the delay-tolerant case in terms of throughput, given that is comparatively giant.

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Compute-and-Forward: Optimization Over Multisource–Multirelay Networks - 4.6 out of 5 based on 54 votes

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