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) fixed base station assignment where the assignment of users to base stations is fixed, (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 finding 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 unifies results found for these systems by identifying common properties of the interference constraints. It is also shown that systems in which transmitter powers ...

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In this paper, we study the problem of joint routing, link scheduling and power control to support high data rates for broadband wireless multi-hop networks. We first address the problem of finding an optimal link scheduling and power control policy that minimizes the total average transmission power in the wireless multi-hop network, subject to given constraints regarding the minimum average data rate per link, as well as peak transmission power constraints per node. Multi-access signal interference is explicitly modeled. We use a duality approach whereby, as a byproduct of finding the optimal policy, we find the sensitivity of the minimal total average power with respect to the average data rate for each link. Since the minimal total average power is a convex function of the required minimum average data rates, shortest path algorithms with the link weights set to the link sensitivities can be used to guide the search for a globally optimum routing. We present a few simple examples that show our algorithm can find policies that support data rates that are not possible with conventional approaches. Moreover, we find that optimum allocations do not necessarily route traffic over minimum energy paths.

The paper considers the problem of m'mimizing the energy used to transmit packets over a wireless link via/azy schedules that judiciously vary packet transmission times. The problem is motivated by the following key observation: In many channel coding schemes, the energy required to transmit a packet can be significantly reduced by lowering transmission power and transmitting the packet over a longer period of time. However, information is often time-critical or delay-sensitive and transmission times cannot be made arbitrarily long. We therefore consider packet transmission schedules that minimize energy subject to a deadline or a delay constraint. Specifically, we obtain an optimal offiine schedule for a node operating under a deadline constraint. An inspection of the form of this schedule naturally leads us to an online schedule which is shown, through simulations, to be energy-efficient. Finally, we relax the deadline constraint and provide an exact probabilistic analysis of our oilline scheduling algoritlun. We then devise a lazy online algoritlun that varies transmission times according to backlog and show that it is more energy efficient than a deterministic schedule that guarantees stability for the same range of arrival rates.

In cellular wireless communication systems, transmitted power is regulated to provide each user an acceptable connection while limiting the interference seen by other users. Previous work has focused on maximizing the minimum carrier to interference ratio (CIR) or attaining a common CIR over all radio links. However, previous work has assumed the assignment of mobiles to base stations is known and fixed. In this work, we integrate power control and base station assignment. In the context of a CDMA system, we consider the minimization of the total transmitted uplink power subject to maintaining an individual target CIR for each mobile. This minimization occurs over the set of power vectors and base station assignments. We show that this problem has special structure and identify synchronous and asynchronous distributed algorithms that find the optimal power vector and base station assignment. Keywords--- Power control, Cellular radio, CDMA, Handoff, Base station assignment I. Introduct...

Abstract—The paper considers the problem of minimizing the energy used to transmit packets over a wireless link via lazy schedules that judiciously vary packet transmission times. The problem is motivated by the following observation. With many channel coding schemes, the energy required to transmit a packet can be significantly reduced by lowering transmission power and code rate, and therefore transmitting the packet over a longer period of time. However, information is often time-critical or delay-sensitive and transmission times cannot be made arbitrarily long. We therefore consider packet transmission schedules that minimize energy subject to a deadline or a delay constraint. Specifically, we obtain an optimal offline schedule for a node operating under a deadline constraint. An inspection of the form of this schedule naturally leads us to an online schedule which is shown, through simulations, to perform closely to the optimal offline schedule. Taking the deadline to infinity, we provide an exact probabilistic analysis of our offline scheduling algorithm. The results of this analysis enable us to devise a lazy online algorithm that varies transmission times according to backlog. We show that this lazy schedule is significantly more energy-efficient compared to a deterministic (fixed transmission time) schedule that guarantees queue stability for the same range of arrival rates. Index Terms—Minimum energy transmission, optimal schedules, power control, wireless LAN. I.

For wireless communication systems, iterative power control algorithms have been proposed to minimize transmitter powers while maintaining reliable communication between mobiles and base stations. To derive deterministic convergence results, these algorithms require perfect measurements of one or more of the following parameters: (i) the mobile's signal to interference ratio (SIR) at the receiver, (ii) the interference experienced by the mobile, and (iii) the bit error rate. However, these quantities are often difficult to measure and deterministic convergence results neglect the effect of stochastic measurements. In this work, we develop distributed iterative power control algorithms that use readily available measurements. Two classes of power control algorithms are proposed. Since the measurements are random, the proposed algorithms evolve stochastically and we define the convergence in terms of the mean squared error (MSE) of the power vector from the optimal power vector that is t...

There has been intense effort in the past decade to develop multiuser receiver structures which mitigate interference between users in spread-spectrum systems. While much of this research is performed at the physical layer, the appropriate power control and choice of signature sequences in conjunction with multiuser receivers and the resulting network user capacity is not well understood. In this paper we will focus on a single cell and consider both the uplink and downlink scenarios and assume a synchronous CDMA (S-CDMA) system. We characterize the user capacity of a single cell with the optimal linear receiver (MMSE receiver). The user capacity of the system is the maximum number of users per unit processing gain admissible in the system such that each user has its quality-of-service (QoS) requirement (expressed in terms of its desired signal-to-interference ratio) met. Our characterization allows us to describe the user capacity through a simple effective bandwidth characterization: Users are allowed in the system if and only if the sum of their effective bandwidths is less than the processing gain of the system. The effective bandwidth of each user is a simple monotonic function of its QoS requirement. We identify the optimal signature sequences and power control strategies so that the users meet their QoS requirement. The optimality is in the sense of minimizing the sum of allocated powers. It turns out that with this optimal allocation of signature sequences and powers, the linear MMSE receiver is just the corresponding matched filter for each user. We also characterize the effect of transmit power constraints on the user capacity.

A distributed power-control algorithm with active link protection (DPC/ALP) is studied in this paper. It maintains the quality of service of operational (active) links above given thresholds at all times (link quality protection). As network congestion builds up, established links sustain their quality, while incoming ones may be blocked and rejected. A suite of admission control algorithms, based on the DPC/ALP one, is also studied. They are distributed/autonomous and operate using local interference measurements.

Distributed power-control algorithms for systems with hard signal-to-interference ratio (SIR) constraints may diverge when infeasibility arises. In this paper, we present a powercontrol framework called utility-based power control (UBPC) by reformulating the problem using a softened SIR requirement (utility) and adding a penalty on power consumption (cost). Under this framework, the goal is to maximize the net utility, defined as utility minus cost. Although UBPC is still noncooperative and distributed in nature, some degree of cooperation emerges: a user will automatically decrease its target SIR (and may even turn off transmission) when it senses that traffic congestion is building up. This framework enables us to improve system convergence and to satisfy heterogeneous service requirements (such as delay and bit error rate) for integrated networks with both voice users and data users. Fairness, adaptiveness, and a high degree of flexibility can be achieved by properly tuning parameters in UBPC.