A Novel Detection Method for Single-RF MIMO-OFDM Systems
2026-06-02 • Information Theory
Information Theory
AI summaryⓘ
The authors propose a new way to detect signals in certain wireless communication systems that use a single radio frequency but multiple antennas. They focus on systems with reconfigurable antennas, which cause some unavoidable errors in the signal. Their method uses a mathematical approach called maximum-likelihood detection with Mahalanobis distance to reduce these errors. Simulations show that their method lowers the error rate better than usual methods when the signal is strong.
Maximum-likelihood detectionMahalanobis distanceSingle-RF MIMOOFDMReconfigurable antennasESPARBit error rateError floorSignal-to-noise ratio
Authors
Tianrui Qiao, Jun Qian, Ross Murch
Abstract
A novel detection method based on maximum-likelihood (ML) detection leveraging Mahalanobis distance is proposed for single-radio-frequency (RF) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. It can enhance bit error rate (BER) performance and is based on the observation that when using reconfigurable antennas (such as electronically steerable parasitic array radiators (ESPARs) to create a single-RF MIMO system, an additional model error arising from the reconfigurable antennas is introduced. These modeling errors produce an irreducible BER (error floor) at high signal-to-noise ratios (SNRs). Simulation results, using ESPAR as an example, validate our error floor analysis and demonstrate that our proposed enhanced detection method can effectively address the error floor and reduce the BER at high transmit SNRs.