Precoder Design with Limited Feedback and Backhauling for Joint Transmission

TL;DR

This paper introduces a precoder design method for joint transmission that leverages long-term channel statistics to reduce feedback and backhaul load while maintaining high throughput, using advanced optimization techniques.

Contribution

It proposes a novel precoder design using long-term channel statistics and successive second order cone programming to optimize weighted sum rate with limited feedback.

Findings

Efficient precoding with reduced feedback and backhaul usage.

Close-to-optimal solutions via SSOCP and weighted MSE minimization.

Comparison shows effectiveness over stochastic methods.

Abstract

A centralized coordinated multipoint downlink joint transmission in a frequency division duplex system requires channel state information (CSI) to be fed back from the cell-edge users to their serving BS, and aggregated at the central coordination node for precoding, so that interference can be mitigated. The control signals comprising of CSI and the precoding weights can easily overwhelm the backhaul resources. Relative thresholding has been proposed to alleviate the burden; however, this is at the cost of reduction in throughput. In this paper, we propose utilizing the long term channel statistics comprising of pathloss and shadow fading in the precoder design to model the statistical interference for the unknown CSI. In this regard, a successive second order cone programming (SSOCP) based precoder for maximizing the weighted sum rate is proposed. The accuracy of the solution obtained is bounded with the branch and bound technique. An alternative optimization framework via weighted mean square error minimization is also derived. Both these approaches provide an efficient solution close to the optimal, and also achieve efficient backhauling, in a sense that the precoding weights are generated only for the active links. For comparison, a stochastic approach based on particle swarm optimization is also considered.