Network-Coded Macrocell Offloading in Femtocaching-Assisted Cellular Networks
KAUST DepartmentElectrical Engineering Program
Permanent link to this recordhttp://hdl.handle.net/10754/626239
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AbstractOpportunistic network coding (ONC) has shown high potential in enhancing the quality-of-experience (QoE) for the clients of cellular networks using their previously downloaded files. In this paper, we study the problem of offloading clients from the macrocell base station (MBS) with the help of femtocaches (FCs) and ONC. We formulate this MBS offloading problem as an optimization problem over an ONC graph, and prove that it is non-deterministic polynomial-time (NP)-hard. Thus, we propose an ONC-broadcast offloading scheme, which utilizes separate ONC graphs at the MBS and FCs in addition to uncoded broadcasting, to offload the clients from the MBS. We analyze the performance of the ONC-broadcast offloading scheme and show that it is asymptotically optimal using random graph theory. Since even this ONC-broadcast offloading scheme is still NP-hard to implement, we devise an efficient heuristic to simplify the implementation. We show that the proposed heuristic reduces the worst-case complexity of implementing the ONC-broadcast offloading scheme from an exponential to a quadratic function of the total number of vertices in the FC ONC graph. Simulation results show that, despite its low complexity, the proposed heuristic achieves similar MBS offloading performance to the ONC-broadcast offloading scheme.
CitationShnaiwer Y, Sorour S, Sadeghi P, Aboutorab N, Al-Naffouri TY (2017) Network-Coded Macrocell Offloading in Femtocaching-Assisted Cellular Networks. IEEE Transactions on Vehicular Technology: 1–1. Available: http://dx.doi.org/10.1109/TVT.2017.2771416.
SponsorsThis research was funded by a grant from the office of competitive research funding (OCRF) at the King Abdullah University of Science and Technology (KAUST). The work was also supported by the Deanship of Scientific Research (DSR) at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, through projects EE002355 and KAUST-002.
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Collaborative Multi-Layer Network Coding For Hybrid Cellular Cognitive Radio NetworksMoubayed, Abdallah J. (2014-05) [Thesis]
Advisor: Alouini, Mohamed-Slim
Committee members: Al-Naffouri, Tareq Y.; Sultan Salem, Ahmed Kamal; Turkiyyah, GeorgeIn this thesis, as an extension to , we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated collaboration between the collocated primary and cognitive radio base-stations in order to minimize their own as well as each other’s packet recovery overheads, thus by improving their throughput. The proposed scheme ensures that each network’s performance is not degraded by its help to the other network. Moreover, it guarantees that the primary network’s interference threshold is not violated in the same and adjacent cells. Yet, the scheme allows the reduction of the recovery overhead in the collocated primary and cognitive radio networks. The reduction in the cognitive radio network is further amplified due to the perfect detection of spectrum holes which allows the cognitive radio base station to transmit at higher power without fear of violating the interference threshold of the primary network. For the secondary network, simulation results show reductions of 20% and 34% in the packet recovery overhead, compared to the non-collaborative scheme, for low and high probabilities of primary packet arrivals, respectively. For the primary network, this reduction was found to be 12%. Furthermore, with the use of fractional cooperation, the average recovery overhead is further reduced by around 5% for the primary network and around 10% for the secondary network when a high fractional cooperation probability is used.