Efficient power control via pricing in wireless data networks

A major challenge in the operation of wireless communications systems is the efficient use of radio resources. One important component of radio resource management is power control, which has been studied extensively in the context of voice communications. With the increasing demand for wireless data services, it is necessary to establish power control algorithms for information sources other than voice. We present a power control solution for wireless data in the analytical setting of a game theoretic framework. In this context, the quality of service (QoS) a wireless terminal receives is referred to as the utility and distributed power control is a noncooperative power control game where users maximize their utility. The outcome of the game results in a Nash (1951) equilibrium that is inefficient. We introduce pricing of transmit powers in order to obtain Pareto improvement of the noncooperative power control game, i.e., to obtain improvements in user utilities relative to the case with no pricing. Specifically, we consider a pricing function that is a linear function of the transmit power. The simplicity of the pricing function allows a distributed implementation where the price can be broadcast by the base station to all the terminals. We see that pricing is especially helpful in a heavily loaded system     

Analysis of a class of distributed asynchronous power controlalgorithms for cellular wireless systems

In cellular wireless communication systems, uplink power control is needed to provide each mobile user with an acceptable signal to interference ratio (SIR) while simultaneously minimizing transmit power levels. We consider a class of distributed asynchronous power control algorithms based on the schemes used in IS-95 inner loop power control. Each user's received SIR is measured (using possibly outdated information) and compared to a threshold, and a single control bit is then sent to the user, indicating whether its power level should be increased or decreased. The SIR measurements and power updates do not require synchronization. We show that under certain conditions, this class of algorithms is stable and converges to a region around the optimal power assignment. We characterize this region and show that it can be made as small as desired by choosing the algorithm parameters appropriately. For an appropriate choice of algorithm parameters, we show that convergence occurs in a finite number of iterations and derive an upper bound. To illustrate our general results, we apply them to systems with fixed base station assignment, dynamic base station assignment, and macrodiversity. Finally, we give an example to illustrate the algorithm's robustness to errors in the power control commands     

多小区无线数据网络中基于最佳等信干比的功率控制

指出多小区无线数据系统中基于非合作博弈的功率控制算法的纳什均衡不是帕累托最优的。提出一种新的适用于多小区无线数据网络的基于最佳等信干比的功率控制算法,使系统中每个小区的终端都工作在最佳等信干比下。仿真结果表明,该算法明显提高了系统的性能,使系统终端具有相对较高的效用和较低的发射功率,并使得无线网络资源的使用更加合理和公平。     

多业务无线网络中基于最佳等信干比的功率控制

功率控制技术是无线网络的关键技术之一。为改进多业务无线网络中基于非合作博弈的功率控制算法中纳什均衡的帕累托有效性,引入数据终端的最佳等信干比概念,使得系统中所有数据终端都工作在最佳的等信干比下,语音终端工作在语音通信服务质量门限的目标信干比门限之下。推导出一个新的分布式基于最佳等信干比的功率控制算法。仿真表明,该算法明显提高了系统的服务质量,系统中终端均具有相对较高的效用和较低的发射功率,还使得无线网络资源的使用更加合理和公平。     

Distributed Uplink Power Control for Optimal SIR Assignment in Cellular Data Networks

This paper solves the joint power control and SIR assignment problem through distributed algorithms in the uplink of multi-cellular wireless networks. The 1993 Foschini–Miljanic distributed power control can attain a given fixed and feasible SIR target. In data networks, however, SIR needs to be jointly optimized with transmit powers in wireless data networks. In the vast research literature since the mid-1990s, solutions to this joint optimization problem are either distributed but suboptimal, or optimal but centralized. For convex formulations of this problem, we report a distributed and optimal algorithm.      

无线数据网络中基于斯塔克尔博格博弈的功率控制

功率控制是无线数据网络中资源管理的关键技术。为使无线数据网络中非合作博弈功率控制算法得到帕累托改进,将斯塔克尔博格博弈引入到无线数据网络功率控制算法中,使所有系统终端都工作在最佳的等信干比下,提出一个基于斯塔克尔博格博弈的分布式功率控制算法,并进行了数值仿真。仿真结果表明,该算法明显提高了系统的性能,使系统终端具有相对较高的效用和较低的发射功率,并使得无线网络资源的使用更加合理和公平,同时算法拥有较好的收敛性。     

Joint network-centric and user-centric radio resource management in a multicell system

A pricing mechanism to mediate (and allocate resources) between conflicting user and network objectives has been recently proposed by the authors in a single-cell system. Here, we extend the results to a multicell system, where the autonomous base station assignment and power control are formulated as a noncooperative game among users. The network prices the resources using two strategies: global pricing that maximizes the revenue, and minimax pricing that trades off the revenue for a more even resource allocation.     

一种基于计费的WCDMA功率控制方法

在第三代移动通信系统中,为了有效地提高系统容量和通信质量,需要对无线资源如发射功率作合理的动态分配。该文通过研究 WCDMA系统中上行链路的干扰情况,推导得出 WCDMA系统的容量与业务性能指标的关系。通过定义网络资源份额,将功率控制问题转换为总量小于1的网络资源份额的分配问题。然后利用统一价格拍卖对网络资源份额进行最优配置,使得发射功率这一重要无线资源合理地分配给对其评价最高的用户业务。最后给出了上述算法的数值仿真。     

基于协议序列的车辆自组织网络信道接入控制算法

 针对如何提高车辆自组织网络无线信道资源利用率问题,提出了一种分布式车辆间通信信道接入控制算法,该算法具体表示为利用中国余数定理设计一种用户保障协议序列,车辆节点(亦称用户)依据该协议序列决定其对通信信道的接入,无需基站或中心节点的协调,所设计的协议序列确保每个车辆节点在一个序列周期内至少成功发送一次数据.仿真结果表明,采用本文提出的协议序列控制算法比无反馈时隙ALOHA接入控制算法具有更小的传输时延,能够满足车辆自组织网络通信实时性的要求.     

Pareto-Efficient and Goal-Driven Power Control in Wireless Networks: A Game-Theoretic Approach With a Novel Pricing Scheme

A Pareto-efficient, goal-driven, and distributed power control scheme for wireless networks is presented. We use a noncooperative game-theoretic approach to propose a novel pricing scheme that is linearly proportional to the signal-to-interference ratio (SIR) and analytically show that with a proper choice of prices (proportionality constants), the outcome of the noncooperative power control game is a unique and Pareto-efficient Nash equilibrium (NE). This can be utilized for constrained-power control to satisfy specific goals (such as fairness, aggregate throughput optimization, or trading off between these two goals). For each one of the above goals, the dynamic price for each user is also analytically obtained. In a centralized (base station) price setting, users should inform the base station of their path gains and their maximum transmit-powers. In a distributed price setting, for each goal, an algorithm for users to update their transmit-powers is also presented that converges to a unique fixed-point in which the corresponding goal is satisfied. Simulation results confirm our analytical developments.     

无线mesh网络中基于效用最优的联合信道分配和功率分配算法

该文针对多信道无线mesh网络,采用基于效用最优的定价机制,提出了一种功率-干扰价格模型,并基于该模型提出了一种分布式联合信道分配和功率分配算法。每个节点根据自己所消耗功率状况合理地定功率价格,并根据自己所受干扰状况合理地定干扰价格。通过功率价格和干扰价格来调节链路的信道分配和功率分配,使网络效用最大化。仿真结果表明:所提出的算法能够快速、平稳地收敛到近似最优解。同时还仿真了网络可用信道数目、节点射频数目和功率对系统性能的影响,可以为网络配置提供参考。     

Single-cell forward link power allocation using pricing in wireless networks

We consider forward link power allocation for voice users in a code-division multiple-access wireless network. Admission control policies are investigated, which base a new call admission decision not only upon available capacity, but also upon the required forward link transmit power and upon the user's willingness to pay. We assume that each voice user has a utility function that describes the user's willingness to pay as a function of forward link signal-to-interference plus noise ratio. The network objective is to maximize either total utility summed over all users or total revenue generated from all users. Properties of the optimal power and code allocations are presented. Our key results show how these optimal allocations can be achieved using pricing. The analysis is complemented with a numerical study, which shows how the optimal prices and corresponding utility or revenue vary with load.     

Packet-Based Power Allocation for Forward Link Data Traffic

We consider the allocation of power across forward-link packets in a wireless data network. The packets arrive according to a random (Poisson) process, and have fixed length so that the data rate for a given packet is determined by the assigned power and the channel gain to the designated user. Each user's service preferences are specified by a utility function that depends on the received data rate. The objective is to determine a power assignment policy that maximizes the time-averaged utility rate, subject to a constraint on the probability that the total power exceeds a limit (corresponding to an outage). For a large, heavily loaded network, we introduce a Gaussian approximation for the total transmitted power, which is used to decompose the power constraint into three more tractable constraints. We present a solution to the modified optimization problem that is a combination of admission control and pricing. The optimal trade-off between these approaches is characterized. Numerical examples illustrate the achievable utility rate and power allocation as a function of the packet arrival rate.     

A game-theoretic approach to decentralized optimal power allocation for cellular networks

The rapidly growing demand for wireless communication makes efficient power allocation a critical factor in the network??s efficient operation. Power allocation in cellular networks with interference, where users are selfish, has been recently studied by pricing methods. However, pricing methods do not result in efficient/optimal power allocations for such systems for the following reason. Because of interference, the communication between the Base Station (BS) and a given user is affected by that between the BS and all other users. Thus, the power vector consisting of the transmission power in each BS-user link can be viewed as a public good which simultaneously affects the utilities of all the users in the network. It is well known (Mas-Colell et al., Microeconomic Theory, Oxford University Press, London, 2002, Chap. 11.C) that in public good economies, standard efficiency theorems on market equilibrium do not apply and pricing mechanisms do not result in globally optimal allocations. In this paper we study power allocation in the presence of interference for a single cell wireless Code Division Multiple Access (CDMA) network from a game theoretic perspective. We consider a network where each user knows only its own utility and the channel gain from the base station to itself. We formulate the uplink power allocation problem as a public good allocation problem. We present a game form the Nash Equilibria of which yield power allocations that are optimal solutions of the corresponding centralized uplink network.     

Hierarchical SIR and rate control on the forward link for CDMA datausers under delay and error constraints

We study the signal-to-interference ratio (SIR) and rate control for code division multiple access (CDMA) data users on the forward link under average or peak power constraints. The quality of service (QoS) for data users is specified by delay and error rate constraints as well as a family of utility functions representing the throughput and fairness among the data users. It is found that the optimal SIR and rate control algorithm has a hierarchical structure which can be easily implemented in a distributed manner. The SIR targets can be adjusted independently by the mobiles using information specific to the individual users. The data rates can be adjusted jointly by the base station based on limited feedback from the mobiles. We also propose a two-level iteration algorithm for both the mobile and the base station to efficiently compute the SIR and data rates. Our results show that a flexible tradeoff between total system throughput (sum of rates achieved) and fairness (similarity in data rates) can be achieved by choosing appropriate utility functions used in this scheme     

Standard and quasi-standard stochastic power control algorithms

In an energy-efficient wireless communication system, transmit powers are minimized subject to predetermined signal-to-interference ratio (SIR) requirements. In this paper, a general framework for distributed stochastic power control (PC) algorithms is proposed, where the transmit powers are updated based on stochastic approximations. The proposed algorithms are distributed in the sense that no global information is needed in the power updates. Interference to each user is estimated locally via noisy observations. Two types of stochastic PC algorithms are studied: standard stochastic PC algorithms where the interference estimator is unbiased, and quasi-standard stochastic PC algorithms where the interference estimator is biased. The conditions under which the stochastic PC algorithms converge to the unique optimal solution are identified. Corresponding to two classes of iteration step-size sequences, two types of convergence, the probability one convergence and convergence in probability, are shown for both algorithms based on recent results in the stochastic approximation literature. Based on the theoretical results, some well-known stochastic PC algorithms, such as stochastic PC with matched filter receivers, and joint stochastic PC with blind minimum mean-squared error (MMSE) interference suppression, are revisited; several new stochastic PC algorithms, such as stochastic PC with minimum-power base-station assignment, and stochastic PC with limited diversity, are proposed. It is shown that these algorithms fall into either the standard or the quasi-standard stochastic PC framework. Simulation results are given to illustrate the performance of the proposed algorithms in practical systems.     

User clustering and robust beamforming design in multicell MIMO-NOMA system for 5G communications

In this paper, we present a robust beamforming design to tackle the weighted sum-rate maximization (WSRM) problem in a multicell multiple-input multiple-output (MIMO) – non-orthogonal multiple access (NOMA) downlink system for 5G wireless communications. This work consider the imperfect channel state information (CSI) at the base station (BS) by adding uncertainties to channel estimation matrices as the worst-case model i.e., singular value uncertainty model (SVUM). With this observation, the WSRM problem is formulated subject to the transmit power constraints at the BS. The objective problem is known as non-deterministic polynomial (NP) problem which is difficult to solve. We propose an robust beamforming design which establishes on majorization minimization (MM) technique to find the optimal transmit beamforming matrix, as well as efficiently solve the objective problem. In addition, we also propose a joint user clustering and power allocation (JUCPA) algorithm in which the best user pair is selected as a cluster to attain a higher sum-rate. Extensive numerical results are provided to show that the proposed robust beamforming design together with the proposed JUCPA algorithm significantly increases the performance in term of sum-rate as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.     

Joint optimization of relay strategies and resource allocations in cooperative cellular networks

This paper considers a wireless cooperative cellular data network with a base station and many subscribers in which the subscribers have the ability to relay information for each other to improve the overall network performance. For a wireless network operating in a frequency-selective slow-fading environment, the choices of relay node, relay strategy, and the allocation of power and bandwidth for each user are important design parameters. The design challenge is compounded further by the need to take user traffic demands into consideration. This paper proposes a centralized utility maximization framework for such a network. We show that for a cellular system employing orthogonal frequency-division multiple-access (OFDMA), the optimization of physical-layer transmission strategies can be done efficiently by introducing a set of pricing variables as weighting factors. The proposed solution incorporates both user traffic demands and the physical channel realizations in a cross-layer design that not only allocates power and bandwidth optimally for each user, but also selects the best relay node and best relay strategy (i.e. decode-and-forward vs. amplify-and-forward) for each source-destination pair     

Automatic Uplink Resource Management in Mobile Cellular Networks: A Utility-Based Cooperative Power Control Strategy

This paper proposes a cooperative power control strategy for resource adaptation in mobile network to optimize user uplink transmission power. Our approach is based on a cooperative model using the economic concepts of utility function and the random graph theory. Based on the model, we develop a distributed power control algorithm that maximizes the utilities of all mobile users. Formulating this algorithm as a cooperative strategy, we show the uncertainty and existence of the power control approach with theory of random bipartite graph and utility function. A discussion to the existence of optimal solutions is given. Then a distributed power control scheme is proposed based on the optimal solutions. It is shown by way of simulation that by introducing utility function in the power control algorithm, there is a performance improvement in terms of the utilities that mobile users obtained. Numerical results are presented for the algorithm.     

WCDMA下行链路分级SIR和速率指配算法研究

研究一种针对WCDMA数据用户的下行链路分级SIR和速率指配算法，其中数据用户的QoS通过时延、误码率以及描述吞吐量和数据用户之间公平性的一族效用函数来表示。算法具有分级控制结构，容易以分布式的形式实现。移动台根据用户特定的本地信息独立地调整SIR目标，而基站根据来自各移动台的有限的反馈信息，同时调整各用户的数据速率。仿真结果表明，通过选择适当的效用函数可以在系统的总吞吐量和公平性之间得到一个灵活的折衷。