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RESEARCH PRODUCT
Joint Topology and Radio Resource Optimization for Device-to-Device Based Mobile Social Networks
Baltasar Beferull-lozanoMohamed Hamidsubject
Random graphSocial networkbusiness.industryComputer scienceNode (networking)05 social sciences050801 communication & media studies020206 networking & telecommunicationsTopology (electrical circuits)02 engineering and technologyIntersection graphNetwork topologyTopologyGraph0508 media and communications0202 electrical engineering electronic engineering information engineeringResource managementEnhanced Data Rates for GSM EvolutionbusinessCommunication channeldescription
In this paper, we consider a joint topology and radio resource optimization for device-to-device (D2D) based mobile social networks. The considered social network is an interest based which is modeled as a d -intersection binomial random graph. The Radio network is also modeled as a random graph where an edge between any two distinct nodes is activated with a certain probability that is equivalent to the probability of exceeding a certain signal to interference ratio for that link. The entire network is then modeled as an intersection graph between the social and radio induced graphs. Thereafter, network topology is optimized such that enabled social edges satisfy certain network connectivity constrains under specific radio environment characteristics. Radio resource allocation is performed to maximize the radio resource utilization exploiting both social ties awareness among the network nodes and knowledge of channel gains among users' locations. We formulate our radio resource allocation problem as a semidefinite program over a graph representing the network topology. Simulation based numerical results are shown in terms of achieved link efficiency and optimized topology parameters. Joint Topology and Radio Resource Optimization for Device-to-Device Based Mobile Social Networks Nivå1
year | journal | country | edition | language |
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2018-04-01 | 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |