Subcarrier grouping with environmental sensing for MIMO-OFDM systems over correlated double-selective fading channels

TL;DR

This paper proposes an adaptive subcarrier grouping algorithm for MIMO-OFDM systems that balances system capacity and resource consumption by leveraging environmental sensing and theoretical analysis of capacity loss.

Contribution

It introduces a theoretical relation between group size and capacity loss and develops an adaptive grouping scheme to optimize system performance.

Findings

Theoretical analysis of capacity loss due to subcarrier grouping.

The proposed algorithm effectively reduces system overburden.

Numerical results show high efficiency in typical scenarios.

Abstract

With the increase of physical antenna and subcarrier numbers in MIMO-OFDM systems, channel side information feedback amount and signal precoding complexity overburden will consume much more system resource, even become intolerable. To solve this problem, previous works mainly focused on fixed subcarrier grouping size and precoded MIMO signals in the same group with unitary channel state information (CSI). It could reduce the system overburden, but such a process would lead to system capacity loss due to the channel mismatch in precoding procedure. In this paper, we consider a MIMOOFDM system over double-selective i.i.d. Rayleigh channels and investigate the quantitative relation between group size and capacity loss theoretically. By exploiting our developed theoretical results, we also propose an adaptive subcarrier grouping algorithm, which not only enables to have a good control of system service quality but also to reduce system overburden significantly. Numerical results are shown to provide valuable insights on the system design of MIMO-OFDM systems and indicate that the proposed subcarrier grouping scheme is extremely efficient in some common scenarios.