Power Control in Wireless Networks

Controlling the transmission power level in a mobile wireless sensor network is an essential process to improve the energy efficiency and quality of service (QoS) at each wireless node. To achieve this goal, we propose to evaluate the QoS by an estimation of the signal-to-interference noise ratio (SINR) according to the IEEE 802.15.4 standard. For this purpose, the received signal strength indicator per packet (RSSIp), and general received signal strength indicator (RSSIg) metrics are considered in this research work followed by a filtering stage to reduce the variability in the SINR estimation. In addition, this research work aims to evaluate different dynamic power control algorithms through an experimental test-bed, where the wireless nodes are in motion. A comparative analysis is presented of five distributed power control algorithms: fixed-step, Foschini-Miljanic, proportional-integral-derivative control, variable structure control, and water-filling control. Moreover, a new distributed power control technique is proposed for mobile wireless sensor networks: modified fixed-step (MFS). All the power allocation algorithms use the tracking error between the estimated and objective SINRs as the driving mechanism to adjust the transmission power. In general, the results show that a dynamic power allocation scheme not only enables the efficient use of the battery, extending its lifetime, but also it is able to achieve the desired QoS despite multiple interference and mobility of the nodes in the network. Furthermore, the results of the experimental evaluation indicate that the modified fixed-step algorithm has the best performance as a function of the reference tracking of the QoS and power consumption.

The problem of power control in wireless networks consists of adjusting transmit power in order to achieve a target SINR level in the presence of noise and interference from other users. In this paper, we examine the performance of the seminal Foschini-Miljanic (FM) power control scheme in networks where channel conditions and users' quality of service (QoS) requirements vary arbitrarily with time (e.g. due to user mobility, fading, etc.). Contrary to the case of static and/or ergodic channels, the system optimum power configuration may evolve over time in an unpredictable fashion, so users must adapt to changes in the wireless medium (or their own requirements) “on the fly”, without being able to anticipate the system evolution. To account for these considerations, we provide a formulation of power control as an online optimization problem and we show that the FM dynamics lead to no regret in this dynamic context. Specifically, in the absence of maximum transmit power constraints, we show that the FM power control scheme performs at least as well as (and typically outperforms) any fixed transmit profile, irrespective of how the system varies with time; finally, to account for maximum power constraints that occur in practice, we introduce an adjusted version of the FM algorithm which retains the convergence and no-regret properties of the original algorithm in this constrained setting.

Power control is a fundamental component of CDMA networks because of the interference that users cause to one another. Consequently, too many users in the system may lead to an overload whereas too few would generate an inefficient use of resources. Previous work by the authors has highlighted some fundamental properties of a CDMA system pertaining to the required power distribution when a particular terminal has reached its power limit. These properties have formed the basis for an admission control scheme which leads to an efficient use of system resources. This paper expands on this scheme and shows that optimal throughput with a fixed number of users can be achieved for a range of received power values and that this range of values is affected by the geometry of the users' location relative to the base station. In addition, there is an optimal number of users and an optimal received power ratio between them that results in maximum throughput. But when the optimal conditions can not be achieved, it is known that equal received power has good performance, and based on this, we design an admission control algorithm.