Variable- $N_{u}$ Generalized Spatial Modulation for Indoor LOS mmWave Communication: Performance Optimization and Novel Switching Structure

Abstract : In this paper, we propose to use variable-N u generalized spatial modulation (VGSM), which is a specific type of generalized spatial modulation, in indoor line-of-sight (LOS) millimeter-wave (mmWave) communication. As compared with fixed-N u generalized spatial modulation, VGSM needs less number of transmitter (TX) antennas to achieve the same data rate. Reducing the number of antennas is especially important for LOS mmWave MIMO communication, since it means reduced array lengths and routing loss in the RF front-end. We first derive and analyze the channel capacity for LOS VGSM, and then propose a novel switching structure for implementation of the VGSM TX at mmWave frequencies and analyze its performance in terms of power added efficiency and capacity. Two optimizations of the system performance of VGSM are performed: 1) power allocation optimization for the proposed TX, and 2) antenna separation optimization in order to optimize the capacity in LOS. Our results show that VGSM is a feasible and promising scheme for indoor LOS mmWave communication. For example, we show that an 8 × 8 VGSM system with practical component values can achieve more than 20bpcu spectral efficiency within a distance of 1-5m and more than 17bpcu within 5-10m.
Document type :
Journal articles
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01879989
Contributor : Frederic Dufaux <>
Submitted on : Monday, September 24, 2018 - 2:01:46 PM
Last modification on : Wednesday, August 7, 2019 - 2:32:05 PM

Identifiers

Citation

Peng Liu, Marco Di Renzo, Andreas Springer. Variable- $N_{u}$ Generalized Spatial Modulation for Indoor LOS mmWave Communication: Performance Optimization and Novel Switching Structure. IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers, 2017, 65 (6), pp.2625 - 2640. ⟨10.1109/TCOMM.2017.2676818⟩. ⟨hal-01879989⟩

Share

Metrics

Record views

33