TY - GEN
T1 - MmWave MIMO-OFDM with Index Modulation: A Pareto-Optimal Trade-off on Spectral-Energy Efficiency
AU - Yang, Yan
AU - Dang, Shuping
AU - Wen, Miaowen
AU - Guizani, Mohsen
N1 - KAUST Repository Item: Exported on 2021-03-09
Acknowledgements: This work was supported by the research task of the State Key Laboratory of Rail Traffic Control and Safety (Contract No. RCS2020ZT012), Beijing Jiaotong University, and the key research task of China Railway Corporation (Contract No. N2019G028).
PY - 2020/12
Y1 - 2020/12
N2 - Multiple-input multiple-output orthogonal frequency division multiplexing with index modulation (MIMO-OFDM-IM) has the potential advantage to balance the trade-off between spectral efficiency (SE) and energy efficiency (EE). This paper investigates the application of MIMO-OFDM-IM to millimeter wave (mmWave) communication systems. Taking advantage of the properties of Pareto optimality, we propose a feasible solution to achieve a globally Pareto-optimal trade-off between SE and EE, and the collision constraints of multi-objective optimization problem (MOP) can be solved efficiently. The MOP of SE-EE trade-off can then be converted into a Pareto-optimal set (POS) solution problem. This combinatorial-oriented resource allocation approach on SE-EE relation considers the optimal beam design and power reallocation for downlink multi-user mmWave transmission. We adopt the Poisson point process (PPP) to model the mobile data traffic, and the evolutionary algorithm is applied to speed up the search efficiency of the Pareto front. Compared with benchmarks, the experimental results collected from extensive simulations reveal that the proposed optimization approach is vastly superior to existing algorithms.
AB - Multiple-input multiple-output orthogonal frequency division multiplexing with index modulation (MIMO-OFDM-IM) has the potential advantage to balance the trade-off between spectral efficiency (SE) and energy efficiency (EE). This paper investigates the application of MIMO-OFDM-IM to millimeter wave (mmWave) communication systems. Taking advantage of the properties of Pareto optimality, we propose a feasible solution to achieve a globally Pareto-optimal trade-off between SE and EE, and the collision constraints of multi-objective optimization problem (MOP) can be solved efficiently. The MOP of SE-EE trade-off can then be converted into a Pareto-optimal set (POS) solution problem. This combinatorial-oriented resource allocation approach on SE-EE relation considers the optimal beam design and power reallocation for downlink multi-user mmWave transmission. We adopt the Poisson point process (PPP) to model the mobile data traffic, and the evolutionary algorithm is applied to speed up the search efficiency of the Pareto front. Compared with benchmarks, the experimental results collected from extensive simulations reveal that the proposed optimization approach is vastly superior to existing algorithms.
UR - http://hdl.handle.net/10754/667940
UR - https://ieeexplore.ieee.org/document/9348046/
UR - http://www.scopus.com/inward/record.url?scp=85101276461&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM42002.2020.9348046
DO - 10.1109/GLOBECOM42002.2020.9348046
M3 - Conference contribution
SN - 9781728182988
BT - GLOBECOM 2020 - 2020 IEEE Global Communications Conference
PB - IEEE
ER -