On Transmit Beamforming for MISO-OFDM Channels With Finite-Rate Feedback

TL;DR

This paper introduces two feedback schemes for transmit beamforming in MISO-OFDM channels with finite-rate feedback, optimizing performance through interpolation and channel quantization methods.

Contribution

It proposes novel feedback strategies combining interpolation and channel quantization, with analytical rate derivations and optimized parameters for improved beamforming performance.

Findings

Interpolation with optimized cluster size outperforms arbitrary cluster size.

Switching between feedback methods yields better performance under different feedback constraints.

Derived approximate sum achievable rates for both proposed feedback schemes.

Abstract

With finite-rate feedback, we propose two feedback methods for transmit beamforming in a point-to-point MISO-OFDM channel. For the first method, a receiver with perfect channel information, quantizes and feeds back the optimal transmit beamforming vectors of a few selected subcarriers, which are equally spaced. Based on those quantized vectors, the transmitter applies either constant, linear, or higher-order interpolation with the remaining beamforming vectors. With constant interpolation, we derive the approximate sum achievable rate and the optimal cluster size that maximizes the approximate rate. For linear interpolation, we derive a closed-form expression for the phase rotation by utilizing the correlation between OFDM subcarriers. We also propose a higher-order interpolation that requires more than two quantized vectors to interpolate transmit beamformers, and is based on existing channel estimation methods. Numerical results show that interpolation with the optimized cluster size can perform significantly better than that with an arbitrary cluster size. For the second proposed method, a channel impulse response is quantized with a uniform scalar quantizer. With channel quantization, we also derive the approximate sum achievable rate. We show that switching between the two methods for different feedback-rate requirements can perform better than the existing schemes.