Interference-Aware Resource Optimization for Device-to-Device Communications in 5G Networks | Zendy

Yuanyuan Hao | Zendy; Qiang Ni | Zendy; Hai Li | Zendy; Shujuan Hou | Zendy; Geyong Min | Zendy

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Interference-Aware Resource Optimization for Device-to-Device Communications in 5G Networks

Author(s) -

Yuanyuan Hao,

Qiang Ni,

Hai Li,

Shujuan Hou,

Geyong Min

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2885035

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In this paper, we investigate the resource optimization problem for device-to-device (D2D) communications in the fifth-generation cellular networks, where multiple D2D links and cellular links share the same spectrum. A general framework is proposed to jointly optimize the energy efficiency (EE), spectral efficiency (SE), and queuing delay. Specifically, we formulate the problem as a stochastic optimization model aiming at maximizing the EE and SE concurrently under the network stability constraint, where subchannel allocation and power control are jointly optimized. Afterwards, with the help of Lyapunov techniques and weighted sum method, it is then transformed into a single-objective optimization problem, which is a mixed-integer and non-convex problem. Therefore, to solve this challenging subchannel allocation and power control problem with low computational complexity, we separate it into two levels of problems, and a two-stage iterative algorithm is proposed, which only requires polynomial computational complexity. Through theoretical analysis and numerical results, the effectiveness, convergence, and optimality of the proposed algorithm are validated.

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