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TLDR

The paper proposes a cross‑layer game‑theoretic framework for joint multiuser detection and power control that maximizes energy efficiency and includes an admission‑control scheme to optimize total network utility. The authors model the uplink DS‑CDMA network as a noncooperative game where each user selects a linear receiver (matched filter, decorrelator, or MMSE) and transmit power to maximize a bits‑per‑joule utility, derive the Nash equilibrium, compare detector utilities, and extend the analysis to multiple antennas and cooperative solutions. They find that the equilibrium occurs when users’ powers are SIR‑balanced with the MMSE detector, yielding the highest bits‑per‑joule utilities compared to matched filter and decorrelator receivers.

Abstract

In this paper, the cross-layer design problem of joint multiuser detection and power control is studied, using a game-theoretic approach that focuses on energy efficiency. The uplink of a direct-sequence code-division multiple-access data network is considered, and a noncooperative game is proposed in which users in the network are allowed to choose their uplink receivers as well as their transmit powers to maximize their own utilities. The utility function measures the number of reliable bits transmitted by the user per joule of energy consumed. Focusing on linear receivers, the Nash equilibrium for the proposed game is derived. It is shown that the equilibrium is one where the powers are signal-to-interference-plus-noise ratio-balanced with the minimum mean-square error (MMSE) detector as the receiver. In addition, this framework is used to study power-control games for the matched filter, the decorrelator, and the MMSE detector; and the receivers' performance is compared in terms of the utilities achieved at equilibrium (in bits/joule). The optimal cooperative solution is also discussed and compared with the noncooperative approach. Extensions of the results to the case of multiple receive antennas are also presented. In addition, an admission-control scheme based on maximizing the total utility in the network is proposed.

References

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