CRB-Based Resource Allocation in Multi-User Uplink Transmissions

TL;DR

This paper investigates receiver design for multi-user uplink systems, deriving CRB-based bounds for channel and symbol estimation, and provides asymptotic analysis and power allocation guidelines to optimize throughput.

Contribution

It introduces CRB-based performance bounds for joint and sequential estimation strategies and uses RMT to derive asymptotic resource allocation guidelines.

Findings

CRB bounds closely approximate mutual information in ideal scenarios.

Asymptotic analysis yields practical power allocation strategies.

Simulation confirms the accuracy of theoretical bounds and guidelines.

Abstract

In this work, we study the design of receivers for uplink multi-user systems, aiming to estimate both the channel and the transmitted symbols. We consider two estimation strategies: (i) a joint estimation approach, where the channel and symbols are estimated simultaneously, and (ii) a sequential estimation approach, where the channel is first estimated and then used for symbol detection. For both strategies, we derive the Cram\'er-Rao Bound (CRB) for symbol estimation to characterize fundamental performance limits. When efficient receivers achieving the CRB exist, these bounds provide accurate lower bounds on the mutual information. In general, however, such receivers may not be available, and we instead use these same CRB-based metrics as practical proxies for achievable throughput. Leveraging tools from random matrix theory (RMT), we analyze the asymptotic behavior of these lower bounds under various asymptotic regimes for both estimation strategies. This analysis enables the derivation of generic power allocation guidelines that asymptotically maximize the proxy metrics. Simulation results confirm the accuracy of the asymptotic expressions and their effectiveness in guiding resource allocation decisions.