Research Article
Energy Efficiency in QoS Constrained 60 GHz Millimeter-Wave Ultra-Dense Networks
@INPROCEEDINGS{10.1007/978-3-030-14413-5_7, author={Huy Nguyen and Homare Murakami and Kien Nguyen and Kentaro Ishizu and Fumihide Kojima and Jong-Deok Kim and Sang-Hwa Chung and Won-Joo Hwang}, title={Energy Efficiency in QoS Constrained 60 GHz Millimeter-Wave Ultra-Dense Networks}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 14th EAI International Conference, Qshine 2018, Ho Chi Minh City, Vietnam, December 3--4, 2018, Proceedings}, proceedings_a={QSHINE}, year={2019}, month={3}, keywords={Millimeter-Wave mmWave Ultra-dense networks Energy efficiency User association Power allocation Penalty Successive convex programming}, doi={10.1007/978-3-030-14413-5_7} }
- Huy Nguyen
Homare Murakami
Kien Nguyen
Kentaro Ishizu
Fumihide Kojima
Jong-Deok Kim
Sang-Hwa Chung
Won-Joo Hwang
Year: 2019
Energy Efficiency in QoS Constrained 60 GHz Millimeter-Wave Ultra-Dense Networks
QSHINE
Springer
DOI: 10.1007/978-3-030-14413-5_7
Abstract
Millimeter-Wave (mmWave) communication in ultra-dense networks (UDNs) has been considered as a promising technology for future wireless communication systems. Exploiting the benefits of mmWave and UDNs, we introduce a new approach for jointly optimizing small-cell base station (SBS) - user (UE) association and power allocation to maximize the system energy efficiency (EE) while guaranteeing the quality of service (QoS) constraints for each UE. The SBS-UE association problem poses a new challenge since it reflects as a complex mixed-integer non-convex problem. On the other hand, the power allocation problem is in non-convexity structure, which is impossible to handle with the association problem concurrently. An alternating descent method is thus introduced to divide the primal optimization problem into two subproblems and handle one-by-one at each iteration, where the SBS-UE association problem is reformulated using the penalty approach. Then, path-following algorithms are developed to convert non-convex problem into the simple convex quadratic functions at each iteration. Numerical results are provided to demonstrate the convergence and low-complexity of our proposed schemes.