Non-Asymptotic Linear Growth of Energy Efficiency in Distributed Autonomous D2D MIMO Wireless Communications

Abstract

Device-to-device (D2D) communications is a cell-free enabler of 5G and rising wireless communications demand between low-orbit satellite constellation, self-driving vehicles and unmanned aerial systems. Distributed computation (where channel state information is not available) schemes facilitate direct exchanges between mobile user equipment (UE) and if necessary a UE can serve as a relay. Thus, it is essential to develop robust D2D communications frameworks agnostic to the channel distribution which can deliver scalable data rates to self-driving vehicles while the spectral efficiency(SE) is non-asymptotic and energy consumption is increasing to yield an energy efficiency (EE) that is a unimodal function. In this paper, we evaluate the optimal EE by using the computation of the SE in distributed multiple input- multiple output (MIMO) wireless communications. A generalized water-filling framework over arbitrary channel distribution is used to evaluate the SE and then the EE to compare with single-input single-output optimized approximate schemes based on Taylor expansion. The computation yields the optimal power allocation at the transmitters which is derived to illustrate the performance gain of the generalized water-filling distributed MIMO over the approximate scheme. Our simulations results show novel achievable EE linear growth as a function of SE and robust trade-offs in performance gains determined by the total power consumption optimal profile when switching MIMO dimensions. Our trade-off prevents power consumption while EE is decreasing. Thus by switching the number of MIMO operating antenna elements at both the receiver and transmitter sides, EE is no more a unimodal function as illustrated in the literature.

Keywords

• Autonomous systems
• D2D communications
• energy efficiency
• MIMO systems
• power control
• spectral efficiency