Abstract
The issue of adaptive and distributed cross-layer resource allocation for energy efficiency in uplink code-division multiple-access (CDMA) wireless data networks is addressed. The resource allocation problems are formulated as noncooperative games wherein each terminal seeks to maximize its own energy efficiency, namely, the number of reliably transmitted information symbols per unit of energy used for transmission. The focus of this paper is on the issue of adaptive and distributed implementation of policies arising from this approach, that is, it is assumed that only readily available measurements, such as the received data, are available at the receiver in order to play the considered games. Both single-cell and multicell networks are considered. Stochastic implementations of noncooperative games for power allocation, spreading code allocation, and choice of the uplink (linear) receiver are thus proposed, and analytical results describing the convergence properties of selected stochastic algorithms are also given. Extensive simulation results show that, in many instances of practical interest, the proposed stochastic algorithms approach with satisfactory accuracy the performance of nonadaptive games, whose implementation requires much more prior information.
Highlights
Introduction and Work MotivationCross-layer design [1, 2] has proven to be an effective tool for improving the performance of wireless data networks
The resource allocation problems are formulated as noncooperative games wherein each terminal seeks to maximize its own energy efficiency, namely, the number of reliably transmitted information symbols per unit of energy used for transmission
In the context of multiuser data networks, such as those based on the code-division multiple-access (CDMA) air interface, cross-layer design has primarily addressed the integration of physical layer issues such as multiuser detection, error correction, and channel estimation, with higher layers functions such as power control, call admission control, packet collision resolution, and so on
Summary
Cross-layer design [1, 2] has proven to be an effective tool for improving the performance of wireless data networks. It should be noted that the solutions proposed in the above-noted studies, providing a general framework for cross-layer resource optimization through a game theoretic approach, describe (and analyze) nonadaptive solutions based on perfect knowledge of a number of parameters such as the spreading codes, the transmit powers, the propagation channels, and the receive filters for all the users, which are assumed to be obtained offline. This kind of information is needed to compute the optimal receiver for each terminal and to compute the received signalto-interference-plus-noise ratio (SINR) for each user, which is needed in the power control updates.
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