IEEE Journal on Selected Areas in Communications · 2017 · 434 citations · 39 references
EngineeringElectrical EngineeringMathematicsEnergy ManagementOptimizationWireless CommunicationsEnergy UseInteger ProgrammingInterference ManagementMillimeter-wave CommunicationsPower OptimizationWireless NetworksCross-tier InterferenceEnergy HarvestingEnergy-efficient CommunicationLagrangian OptimizationMixed-integer ProgrammingPower AllocationRadio Resource AllocationSpectral Efficiency
Millimeter‑wave (mmWave) technology is emerging to meet the growing mobile data demand, and ultra‑dense networks (UDNs) using mmWave are expected to boost both energy and spectral efficiency. This study aims to design user association and power allocation strategies for mmWave‑based UDNs that satisfy load‑balance, energy‑harvesting, QoS, energy‑efficiency, and interference constraints. The joint problem is formulated as a mixed‑integer program, relaxed to a convex problem, and solved via Lagrangian dual decomposition with an iterative gradient algorithm that converges rapidly. Simulations show the algorithm converges quickly to an optimal point, with lower complexity and superior performance compared to existing methods.
Millimeter wave (mmWave) communication technologies have recently emerged as an attractive solution to meet the exponentially increasing demand on mobile data traffic. Moreover, ultra dense networks (UDNs) combined with mmWave technology are expected to increase both energy efficiency and spectral efficiency. In this paper, user association and power allocation in mmWave-based UDNs is considered with attention to load balance constraints, energy harvesting by base stations, user quality of service requirements, energy efficiency, and cross-tier interference limits. The joint user association and power optimization problem are modeled as a mixed-integer programming problem, which is then transformed into a convex optimization problem by relaxing the user association indicator and solved by Lagrangian dual decomposition. An iterative gradient user association and power allocation algorithm is proposed and shown to converge rapidly to an optimal point. The complexity of the proposed algorithm is analyzed and its effectiveness compared with existing methods is verified by simulations.
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MmWave massive-MIMO-based wireless backhaul for the 5G ultra-dense network
Zhen Gao, Linglong Dai, De Mi et al. · IEEE Wireless Communications · 2015 · 448 citations · Full text