Robust H_?Power Control for CDMA Systems in User-Centric and Network-Centric Manners

Abstract

In this paper, we present a robust H∞ distributed power control scheme for wireless CDMA communication systems. The proposed scheme is obtained by optimizing an objective function consisting of the user's performance degradation and the network interference, and it enables a user to address various user‐centric and network‐centric objectives by updating power in either a greedy or energy efficient manner. The control law is fully distributed in the sense that only its own channel variation needs to be estimated for each user. The proposed scheme is robust to channel fading due to the immediate decision of the power allocation of the next time step based on the estimations from the H∞ filter. Simulation results demonstrate the robustness of the scheme to the uncertainties of the channel and the excellent performance and versatility of the scheme with users adapting transmit power either in a user‐centric or a network‐centric efficient manner.

Energy‐efficient power allocation algorithm in cognitive radio networks

“…Each user should achieve the value above a certain target value. We obtain in [18] which may be considered as a user‐centric metric or SINR tracking metric since it represents the deviation between the cognitive user's time‐varying target SINR of and the received SINR of . In accordance with the QoS of the cognitive user, we should guarantee greater as .…”

Analysis of distributed power allocation in wireless networks under multiplicative noise and interference uncertainty

“…In the previous result, it is considered that the linear distributed controllers C i (z) are known a priori, for example PID control [28], Foschini-Miljanic algorithm [9], robust smith predictor [17], H ∞ power control [15], [31], or LQG control [5]. To illustrate this idea, the LQG control derived in [5] which takes into account the round-trip delay n RT and has important robustness properties is addressed in this work.…”

“…For CDMA and MC-CDMA wireless networks [8], [21], [25], there have been important contributions in power control or management [14], for example game-theory or teamoptimization approaches [1], [22], passivity-based control [7], robust Smith predictor [17], switched-PID control [28], LQG algorithm [5], and H ∞ controllers [15], [31]. Recently, the problems of power control under the effect of additive random noise due to quantization in the feedback path and signal-to-noise ratio limitations have been addressed in [4] and [27].…”

Population Declining Ant Colony Optimization Multiuser Detection in Asynchronous CDMA Communications

“…In practice, the SEBs b (i− 1) in (8) can be derived from the previous detection process and if the desired bit-error probability of the receiver is sufficiently low, it can be assumed that the SEBs b (i−1) are perfectly known. Hence, we can optimize (8) with respect to the desired b (i) and EEBs b (i+1) , yielding the objective function of OMD given as…”