Location-Aided Maximal Ratio Combining for an Acoustic Vector Sensor in Multipath Channels
Xinghao Qu, Zhigang Shang, Gang Qiao, Yiwen Zhou · IEEE Signal Processing Letters · 2025
The multi-channel outputs of an acoustic vector sensor (AVS) provide diversity gain for communications, and developing an effective combining scheme becomes a critical issue. However, in underwater multipath channels, a single AVS struggles to estimate the spatial signatures of multipath signals due to its limited sensing capability, which compromises the design of optimal combining weights. To overcome this issue, we propose a location-aided maximal ratio combining (MRC) technique. Armed with a predictable end-to-end propagation model, we first develop a maximum-likelihood sensing framework with the help of the pilot subcarriers embedded in the OFDM signal. The required channel state information is inferred from the estimated propagation geometry. Then, the combining weight vector is determined according to the MRC principle. Simulations demonstrate that this integrated scheme enhances communication performance through comprehensive environmental sensing.