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Resource allocation for licensed and unlicensed spectrum in 5G heterogeneous networks
Author(s) -
Ali Mudassar,
Qaisar Saad,
Naeem Muhammad,
Rodrigues Joel J. P. C.,
Qamar Farhan
Publication year - 2018
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.3299
Subject(s) - computer science , throughput , spectrum management , benchmark (surveying) , resource allocation , computer network , interference (communication) , optimization problem , cellular network , radio resource management , key (lock) , cognitive radio , telecommunications , wireless network , wireless , algorithm , computer security , channel (broadcasting) , geodesy , geography
Abstract The foresighted enormous increase in mobile traffic over the coming years will result in severe congestion on available radio spectrum. The use of additional spectrum in future fifth‐generation mobile networks will be inevitable. Long‐Term Evolution Unlicensed (LTE‐U) is an evolving technology, which effectively utilizes available unlicensed spectrum to increase the capacity of unified fifth‐generation network. However, LTE‐U causes severe interference to existing WiFi networks, which needs to be addressed to take full advantage of LTE‐U. In this paper, we thrive to provide a suboptimal resource allocation for coexisting LTE‐U and WiFi networks to maximize throughput and, hence, minimize the interference. We formulated an optimization problem for joint user association and power allocation for licensed and unlicensed spectrum with objective to maximize sum rate of LTE‐U/WiFi heterogeneous network in a multioperator scenario, subject to minimum rate guarantee and cochannel interference threshold. We propose mesh adaptive direct search algorithm as solution to optimization problem to obtain ϵ ‐optimal results. The performance of proposed algorithm is shown in terms of network key performance indicators such as throughput and number of users accommodated. We also benchmark the results from mesh adaptive direct search against outer approximation algorithm.