Coverage analysis using the Poisson point process model

Mukherjee, Sayandev

doi:10.1017/cbo9781139061421.005

Cited by 1 publication

(2 citation statements)

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“…The surge of computational power, algorithms, and new coding approaches makes it possible to solve modest-size convex optimization problems in microsecond or millisecond scales [47], [48]. Hence, the computational complexity of the power allocation solution given in (21) would not pose a difficulty in practice. The preliminary algorithm based on interior-point methods [49] is summarized in Algorithm 1, and an interior-point solver to (21) -( 22), which combines line search and trust region steps [50], is available in Matlab optimization toolbox.…”

Section: B Problem Formulation and Convex Optimizationmentioning

confidence: 99%

“…However, interference observed at a given location is temporally and/or spatially correlated, ignoring this correlation by only considering the coverage probability of a typical link may lead to the incorrect characterization of network performance [20]. To identify such correlation, the joint coverage probability, namely joint complementary cumulative distribution function (CCDF) of SINR, has been used to study the joint statistics across space or time [21]- [23].…”

Section: Introductionmentioning

confidence: 99%

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Joint Coverage Enhancement by Power Allocation in Poisson Clustered Out-of-Band D2D Networks

Tang

Chen

Coon

2018

IEEE Trans. Veh. Technol.

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In this paper, we consider a Poisson clustered outof-band device-to-device (D2D) network operating in Rayleigh fading channels and propose two optimization schemes based on the joint coverage probability to allocate the transmit power to D2D user equipments (DUEs) in both the target cluster and the whole network. The joint coverage probability accounts for the spatial correlation of the interference among the DUEs. With a differing amount of location information being available among the DUEs in centralized and localized communication solutions, the joint coverage probability is formulated based on the coherent, non-coherent, and single-cluster approximated pairwise coverage probabilities. By maximizing the joint coverage probability formulated in this way, the robustness of the network can be enhanced. Meanwhile, to fulfill the green aspect of future 5G communications, the battery life of the DUEs will be prolonged by minimizing the power consumption for a given joint coverage probability requirement. The formulations of the two optimization problems above are not convex but are transformed to convex by using geometric programming. The simulation results show that, compared with the conventional LTE open loop and fixed power schemes, the joint coverage probability and power consumption are respectively optimized by applying the proposed schemes.

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