A framework for uplink power control in cellular radio systems

Abstract

In cellular wireless communication systems, transmitted power is regulated to provide each user an acceptable connection by limiting the interference caused by other users. Several models have been considered including: (1) xed base station assignment where the assignment of users to base stations is xed, (2) minimum power assignment where a user is iteratively assigned to the base station at which its signal to interference ratio is highest, and (3) diversity reception, where a user's signal is combined from several or perhaps all base stations. For the above models, the uplink power control problem can be reduced to nding a vector p of users' transmitter powers satisfying p I(p) where the jth constraint p j I j (p) describes the interference that user j must overcome to achieve an acceptable connection. This work uni es results found for these systems by identifying common properties of the interference constraints. It is also shown that systems in which transmitter powers are subject to maximum power limitations share these common properties. These properties permit a general proof of the synchronous and totally asynchronous convergence of the iteration p(t + 1) = I(p(t)) to a unique xed point at which total transmitted power is minimized.

Maximizing sum rate and minimizing MSE on multiuser downlink: Optimality, fast algorithms and equivalence via max-min SIR

“…We will leverage the standard interference function results in [11] to propo se the following (step size free) algorithm that computes z* in Theorem 4, and implicitly, the optimal transmit power of (18).…”

“…Remark 5: The convergence of Algorithm 3 leverages the standard interference function approach in [11] by introducing E in (26) of Algorithm 3.…”

“…As in the previous, (31) in Theorem 7 can be expressed as z == I(z), where I is a homogeneous function. Using the standard interference function approach in [11], the following algorithm computes the optimal solution of (28).…”

“…However, due to (8), the standard interference function approach in [11] cannot be used to prove the convergence of Algorithm 1.…”

Power Control in Cognitive Radio Networks Using Cooperative Modulation and Coding Classification

“…Based on this, a central decision maker, the Base Station, gathers local information from the users through a control channel, elaborates an intelligent selection of their operational parameters, such as their transmit power, channel or time schedule, and communicates it to them. In this general context, the research community has formulated and tackled PC problems [9][10][11][12][13][14] to achieve common or different signal to interference plus noise ratio (SIN R) requirements, maximum total system throughput, maximum weighted throughput, maximum worst user throughput or minimum transmit power, subject to QoS constraints from individual users, like SIN R, data rate or outage probability. In the CR regime, the centralized PC problem retains its basic form but with some small alterations.…”