On Optimal Policies for Network Coded Cooperation : Theory and Implementation

• Tipo: Artigo em Revista Científica Internacional
• Data: 2014

Autores

Hana Khamfroush (Autor) FEUP; Daniel Lucani (Autor) Outra; Pahlevani, P. (Autor) Outra; João Barros (Autor) FADEUP

Revista

Título: IEEE Journal on Selected Areas in Communications

ISSN: 0733-8716

Editora: IEEE

Indexação

ISI Web of Science

Classificação Científica

FOS: Ciências da engenharia e tecnologias

Outras Informações

DOI: 10.1109/JSAC.2014.2384291

Abstract (EN): Network coded cooperative communication (NCCC) has been proposed and evaluated as a powerful technology that can provide a better quality of service in the next generation wireless systems, e.g., D2D communications. Previous contributions have focused on performance evaluation of NCCC scenarios rather than searching for optimal policies that can minimize the total cost of reliable packet transmission. We break from this trend by initially analyzing the optimal design of NC-CC for a wireless network with one source, two receivers and half duplex erasure channels. The problem is modelled as a special case of Markov decision process (MDP), called stochastic shortest path (SSP), and is solved for any field size, arbitrary number of packets, and arbitrary erasure probabilities of the channels. The proposed MDP solution results in an optimal transmission policy per time slot and we use it to design nearoptimal heuristics for packet transmission in a network of one source and N 2 receivers. We also present numerical results that illustrate the performance of the proposed heuristics under a variety of scenarios. To complete our analysis, our heuristics are implemented in Aalborg University’s Raspberry Pi test-bed and compared with random linear network coding (RLNC) broadcast in terms of completion time, total number of required transmissions, and percentage of delivered generations. Our measurements show that enabling cooperation only amongst pairs of devices can decrease the completion time by up to 4:75 times while delivering 100% of the 10000 generations transmitted, compared to RLNC broadcast delivering only 88% of them in our tests.

Idioma: Inglês

Tipo (Avaliação Docente): Científica