Abstract
This paper addresses the problem of joint resource allocation in general wireless networks and its practical implementation aspects. The objective is to allocate transmit powers and receive beamformers to the users in order to maximize a network-wide utility that represents the attained QoS and is a function of the signal-to-interference ratios. This problem is much more intricate than the corresponding QoS-based power control problem. In particular, it is not known which class of utility functions allows for a convex formulation of this problem. In case of perfect synchronization, the joint power and receiver control problem can be reformulated as a power control problem under optimal receivers. Standard gradient projection methods can be applied to solve this problem. However, these algorithms are not applicable in decentralized wireless networks. Therefore, we decompose the problem and propose a convergent alternate optimization that is amenable to distributed implementation. In addition, in real-world networks noisy measurements and estimations occur. Thus, the proposed algorithm has to be investigated in the framework of stochastic approximation. We discuss practical implementation aspects of the proposed stochastic algorithm and investigate its convergence properties by simulations.
Highlights
Two central mechanisms for resource allocation and interference management in wireless networks are power control and beamforming
This paper addresses the problem of joint resource allocation in general wireless networks and its practical implementation aspects
Apart from that, so far most work on joint power control and beamforming has focused on the QoS-based resource allocation, especially on the so-called max-min signal-to-interference ratio (SIR)-balancing and its related problem
Summary
Two central mechanisms for resource allocation and interference management in wireless networks are power control and beamforming. The authors of [18] interpret the utility-based power control problem as a joint optimization of powers and SIR assignment over the feasibility region They proposed a distributed power control and SIR assignment algorithm for the uplink in a multicell wireless network. From and simultaneously to our work the authors of [19] have proposed a distributed utility-based joint power control and receive beamforming algorithm for cellular uplinks applying the scheme of [18]. Apart from that, so far most work on joint power control and beamforming has focused on the QoS-based resource allocation, especially on the so-called max-min SIR-balancing and its related problem. In contrast to the pure power control problem [14], it is not known which class of utility functions allows a convex formulation of this joint optimization problem and enables an efficient global solution in distributed wireless networks. These base stations create a wireless backbone via multihop ad hoc networking and have practically unlimited energy supply
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