This paper proposes a novel method for device-to-device (D2D) user clustering that allows wireless users in proximity to share common resources to save both system bandwidth and energy resources. The idea at the basis of our proposed cluster formation is to incorporate both social interactions and physical relationships among D2D terminals. Towards this goal, we propose two clustering approaches. The first one is based on the Chinese restaurant process (CRP), whereas the second one enhances the traditional CRP by defining a "distance-dependent Chinese restaurant process" (namely, DCRP). Numerical simulation results demonstrate superiority of our proposed clustering schemes in terms of system throughput, energy consumption, and energy efficiency over the existing schemes that rely only on physical distance.

Device-to-Device Users Clustering Based on Physical and Social Characteristics / Wang, L; Araniti, Giuseppe; Cao, Cy; Wang, W; Liu, Y. - In: INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS. - ISSN 1550-1477. - 2015:2015(2015), pp. 1-14. [10.1155/2015/165608]

Device-to-Device Users Clustering Based on Physical and Social Characteristics

ARANITI, Giuseppe;
2015-01-01

Abstract

This paper proposes a novel method for device-to-device (D2D) user clustering that allows wireless users in proximity to share common resources to save both system bandwidth and energy resources. The idea at the basis of our proposed cluster formation is to incorporate both social interactions and physical relationships among D2D terminals. Towards this goal, we propose two clustering approaches. The first one is based on the Chinese restaurant process (CRP), whereas the second one enhances the traditional CRP by defining a "distance-dependent Chinese restaurant process" (namely, DCRP). Numerical simulation results demonstrate superiority of our proposed clustering schemes in terms of system throughput, energy consumption, and energy efficiency over the existing schemes that rely only on physical distance.
2015
D2D, Clustering, Social proximity
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/3438
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