Designing and Optimizing Swarming in a Distributed Base Station Network: Application to Power Control
Todays' networks are becoming increasingly complex. They must provide a growing variety of services to a wide range of devices. In order to do so, they must make efficient use of modern technologies including MIMO, macrodiversity, power control, channel allocation, beamforming, and so on. In this context, the centralized management of radio resources on a large scale is rapidly becoming intractable. Distributed intelligence constitutes an increasingly attractive solution to provide network-wide self-configuration and adaptation capabilities. This article presents the design of a swarming system for autonomous power control which adapts naturally to the changing conditions of mobile networks where interference patterns are in constant flux. Empirical methods proposed by Parunak [1997] to develop MultiAgent Systems with Swarming (MASS) are applied to the current context while emphasizing the key concepts that lead to swarming (emergent behavior). A simulation-based study reveals how the system can be fine-tuned to obtain various solutions, balancing resources differently to achieve different trade-off points. Finally, it is shown that the distributed approach based on swarming is not only feasible but leads to higher global QoS levels than comparable centralized approaches.
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