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In this letter, we present a two-phase distributed resource allocation algorithm for a Device-to-Device (D2D) network underlaying a cellular network. In the first phase, D2D pairs learn resource block (RB) of the cellular user equipment (CUEs) to be used, while playing an interference minimization game. Each D2D pair is ensured an interference below an upper limit, which is chosen as the criterion...
We investigate the problem of resource block (RB) and power allocation jointly and in a distributed manner using game theoretic learning solutions, in an underlay device-to-device network where device pairs communicate directly with each other by reusing the spectrum allocated to the cellular users. We formulate the joint RB and power allocation as multi-agent learning problems with discrete strategy...
This paper investigates distributed resource allocation in next-generation underlay Device-to-Device (D2D) networks. The joint channel and power allocation for a D2D network underlaying a cellular network is formulated as a non-cooperative game. A utility-based learning algorithm which does not require information exchange between device pairs is proposed to determine the channel index and power level...
This paper investigates the problem of distributed joint channel and power allocation using game theoretic learning solutions in an underlay Device-to-Device (D2D) network where device pairs communicate directly with each other by reusing the spectrum that is being used by cellular users. This reuse, in addition to increasing the capacity, results in new cross-tier and co-tier interference cases....
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