Power-Efficient Resource Allocation for Time-Division Multiple Access Over Fading Channels

We investigate resource allocation policies for time-division multiple access (TDMA) over fading channels in the power-limited regime. For frequency-flat block-fading channels and transmitters having full channel state information (CSI), we first minimize power under a weighted sum average rate constraint and show that the optimal rate and time allocation policies can be obtained by a greedy water-filling approach with linear complexity in the number of users. Subsequently, we pursue power minimization under individual average rate constraints and establish that the optimal resource allocation also amounts to a greedy water-filling solution. Our approaches not only provide fundamental power limits when each user can support an infinite-size capacity-achieving codebook (continuous rates), but also yield guidelines for practical designs where users can only support a finite set of adaptive modulation and coding modes (discrete rates).      

Iterative multiuser uplink and downlink beamforming under SINR constraints

We study the problem of power efficient multiuser beamforming transmission for both uplink and downlink. The base station is equipped with multiple antennas, whereas the mobile units have single antennas. In the uplink, interference is canceled by successive decoding. In the downlink, ideal "dirty paper" precoding is assumed. The design goal is to minimize the total transmit power while maintaining individual SINR constraints. In the uplink, the optimization problem is solved by a recursive formula with low computational complexity. The downlink problem is solved by exploiting the duality between uplink and downlink; thus, the uplink solution carries over to the downlink. In the second part of the paper, we show how the solution can be applied to the problem of rate balancing in Gaussian multiuser channels. We propose a strategy for throughput-wise optimal transmission for broadcast and multiple access channels under a sum power constraint. Finally, we show that single-user transmission achieves the sum capacity in the low-SNR regime. We completely characterize the SNR-range where single-user transmission is optimal.     

Optimal resource allocation for multiple network‐coded two‐way relay in orthogonal frequency division multiplexing systems

This paper studies optimal resource allocation for multiple network‐coded two‐way relay in orthogonal frequency division multiplexing systems. All the two‐way relay nodes adopt amplify‐and‐forward and operate with analog network coding protocol. A joint optimization problem considering power allocation, relay selection, and subcarrier pairing to maximize the sum capacity under individual power constraints at each transmitter or total network power constraint is first formulated. By applying dual method, we provide a unified optimization framework to solve this problem. With this framework, we further propose three low‐complexity suboptimal algorithms. The complexity of the proposed optimal resource allocation (ORA) algorithm and three suboptimal algorithms are analyzed, and it is shown that the complexity of ORA is only a polynomial function of the number of subcarriers and relay nodes under both individual and total power constraints. Simulation results demonstrate that the proposed ORA scheme yields substantial performance improvement over a baseline scheme, and suboptimal algorithms can achieve a trade‐off between performance and complexity. The results also indicate that with the same total network transmit power, the performance of ORA under total power constraint can outperform that under individual power constraints. Copyright © 2012 John Wiley & Sons, Ltd.     

Resource allocation in underlay cognitive radio networks with full‐duplex cognitive base station

This paper considers an underlay cognitive radio network with a full‐duplex cognitive base station and sets of half‐duplex downlink and uplink secondary users, sharing multiple channels with the primary user. The resource allocation problem to maximize the sum rate of all the secondary users is investigated subject to the transmit power constraints and the interference power constraint. The optimization problem is highly nonconvex, and we jointly use the dual optimization method and the successive convex approximation method to derive resource allocation algorithms to solve the problem. Extensive simulations are shown to verify the performance of the resource allocation algorithms. It is shown that the proposed algorithms achieve much higher sum rate than that of the optimal half‐duplex algorithms and the reference full‐duplex algorithms.     

Joint Beamforming and Power Allocation for Cognitive MIMO Systems Under Imperfect CSI Based on Game Theory

The problem of joint beamforming and power allocation for cognitive multi-input multi-output systems is studied via game theory. The objective is to maximize the sum utility of secondary users (SUs) subject to the primary user (PU) interference constraint, the transmission power constraint of SUs, and the signal-to-interference-plus-noise ratio (SINR) constraint of each SU. In our earlier work, the problem was formulated as a non-cooperative game under the assumption of perfect channel state information (CSI). Nash equilibrium (NE) is considered as the solution of this game. A distributed algorithm is proposed which can converge to the NE. Due to the limited cooperation between the secondary base station (SBS) and the PU, imperfect CSI between the SBS and the PU is further considered in this work. The problem is formulated as a robust game. As it is difficult to solve the optimization problem in this case, existence of the NE cannot be analyzed. Therefore, convergence property of the sum utility of SUs will be illustrated numerically. Simulation results show that under perfect CSI the proposed algorithm can converge to a locally optimal pair of transmission power vector and beamforming vector, while under imperfect CSI the sum utility of SUs converges with the increase of the transmission power constraint of SUs.     

Optimal Uplink Power Control in Two-Cell Systems with Rise-over-Thermal Constraints

Joint assignment of transmit powers to users through basestation cooperation improves system capacity. In this letter, we study the optimal power allocation for sum capacity in a two-cell system with an individual rise-over-thermal constraint per basestation. It is proven that the optimal power allocation to any pair of users resides in one of five discrete power assignments, each of which corresponds to at least one constraint being binding. We propose a joint proportional fairness scheduler across two cells that extends the optimal power allocation to multi-user systems. Simulations show that the combined power allocation and proportional fairness scheduler achieves significant gains over a conventional round-robin scheduler, in terms of both cell average and cell edge throughput.     

Robust uplink power control for co-channel two-tier femtocell networks

This paper is concerned with uplink interference suppression problem in two-tier femtocell networks through power control. Specifically, we consider the Quality-of-Service (QoS) of the macrocell user and femtocell users in terms of their received Signal to Interference-plus-Noise Ratios (SINRs) at macrocell base station (MBS) and femtocell base stations (FBSs), and we also take femtocell users’ power efficiency into consideration by designing an objective function, which is a weighted sum of transmission power and squared SINR difference between femtocell user's maximum SINR and actual SINR. Due to the error of the SINR at MBS caused by distance errors, a robust uplink power control problem is formulated, and it is equivalent to a robust convex optimization problem with femtocell users’ SINR constraints. Then, the robust convex optimization problem is converted into a general convex optimization problem. Moreover, a distributed power control algorithm combined with admission control is presented to obtain femtocell users’ optimal power allocation. Numerical results show the convergence and effectiveness of the proposed uplink power control algorithm.     

多用户MIMO系统最优发送策略研究

研究一个收发双方都采用多天线的K用户MIMO系统的前向链路的几种最优发送策略.利用矢量广播信道和矢量多接入信道之间的对偶性交换两类信道的发送协方差矩阵以达到快速优化;分析了在各用户功率受限时总的信道容量最大的算法;研究在假定基站采用理想的线性多用户MMSE接收时的最优发送.在总功率受限时通过调整各用户的协方差矩阵实现平均标准MSE最优,采用自适应功率分配可以进一步优化MSE.分析最优化问题与KKT条件的关系,通过迭代计算单用户平均最小均方误差,利用内点法计算互协方差矩阵优化问题.     

OFDMA上行链路中基于博弈论的子载波和功率分配算法

传统OFDMA上行链路资源分配算法中一般以最大化各用户速率或最小化发射功率为依据对子载波和功率进行分配,而对于各用户的功率效率问题并没有加以考虑。针对这一问题,该文提出了一种基于功率效率最优的联合子载波功率分配算法。首先给出了在各用户峰值功率约束条件下达到收益函数最优的必要条件并证明了算法纳什均衡的存在及唯一性,然后给出了子载波功率分配算法。仿真表明:相比最大边界速率子载波和功率分配算法(MaxRt+WF)和固定子载波和功率分配算法(MaxFA+WF),该文算法能大幅度提高各用户的功率效率。同时如果合理地选择代价参数,算法获得的和功率效率能够达到更大。     

Jointly optimizing sensing time and resource allocation in multichannel cognitive radio networks

Spectrum sensing is a key technique for determining the spectrum available in cognitive radio (CR) networks. In this paper, we study how to jointly optimize sensing time and resource allocation to maximize the sum transmission rate of all CR users of a multichannel CR network. We take into consideration the transmission power and interference constraints to protect primary users from harmful interference, as well as constraints of detection probability and false alarm probability. Under these constraints, we propose an asymptotically optimal resource allocation algorithm. The optimal sensing time can be obtained using the traditional one‐dimensional exhaustive search. However, owing to the high complexity of searching for the sensing time, we propose a simplified method to get the optimal sensing time under the assumption that false alarm probability is small. Simulation results show that the simplified method can obtain the optimal sensing time efficiently under strict constraint of false alarm probability. Copyright © 2012 John Wiley & Sons, Ltd.     

Stochastic power allocation using causal channel information for delay-limited communications

Without delay constraints, ergodic capacity can be achieved through channel coding over time frames spanning the whole fading process of the channel without the need of channel state information (CSI) at the transmitter. If the channel capacity is delay-constrained, then causal CSI at the transmitter becomes important. In this letter, our aim is to resolve the optimal power-and-rate allocation in maximizing the expected capacity subject to total power constraint, given the causal CSI at the transmitter. The proposed solution is adaptive to the current and past CSI, and also the statistics of the future channels. Asymptotically in both the high and low signal-to-noise ratio (SNR) regimes, we show that at a particular constant in time, the optimal power policy has an interpretation of water-filling among the current channel and some estimates of the future channels     

非理想信道状态信息的认知无线网络下行功率分配和波束赋形方法

针对非理想信道状态信息(CSI)条件下工作于underlay模式的认知无线网络(CRN)多用户下行功率分配和波束赋形研究中普遍存在的问题,包括忽略主网络(PN)对认知用户(SU)的干扰、传统的凸优化SDR方法对约束条件的近似要求以及实现算法复杂、实用性受限等,首先建立CRN模型,增添PN对SU的干扰项,而后在非理想CSI的最差条件下形成优化问题。再通过Lagrange对偶对问题的约束条件进行变换,并基于变换后的问题形式,利用上行和下行的对偶特性,引入虚拟功率,将优化问题转换为上行功率分配和波束赋形问题,进一步得到简便、快速和实用的迭代算法。数值仿真显示,算法收敛很快。并且发现非理想CSI引起的误差不仅对下行功率影响明显而且还改变优化问题的可行解区域;PN基站(PBS)的发送功率的变化对可行解区域有显著的影响。     

Design of Optimal Linear Precoder and Decoder for MIMO Channels with Per Antenna Power Constraint and Imperfect CSI

This paper addresses the problem of designing joint optimum precoder and decoder for multiple-input multiple-output communication system. Conventionally, most of the joint precoder and decoder designs are based on the sum power constraint (SPC) at the transmitter and perfect channel state information (CSI). However, in practice, per-antenna power constraint is more realistic as the power at each transmit antenna is limited individually by the linearity of the power amplifier. Further, the estimate of CSI cannot be obtained perfectly by any methods. Under imperfect CSI, the aim is to design jointly optimum precoder and decoder subject to a power constraint that jointly meets both per-antenna and SPCs. The objective function is formulated into an optimization problem that minimizes the mean square error in estimating the transmitted signal. The simulation results show that the proposed scheme has a near-optimum performance under practical constraints.     

Joint subcarrier and power allocation in uplink OFDMA systems

In this letter, we focus on joint subcarrier and power allocation in the uplink of an OFDMA system. Our goal is to maximize the rate-sum capacity in the uplink. For the purpose, we formulate an optimization problem subject to subcarrier and power constraints and draw necessary conditions for optimality, from which we derive joint subcarrier and power allocation algorithms. Simulation results show that our proposed scheme enhances the system capacity, providing almost near optimal solutions with low computational burden.     

Power control for delay constrained multi‐channel communications using outdated CSI

In this paper, we study the power allocation scheme for a single user, multi‐channel system, e.g., orthogonal frequency‐division multiplexing (OFDM) systems, under time‐variant wireless fading channels. We assume the receiver feeds back perfectly estimated channel state information (CSI) to the transmitter after a processing delay. The objective of the power allocation is to maximize throughput subject to quality‐of‐service (QoS) constraint. The QoS measure of our consideration is a triplet of data rate, delay, and delay bound violation probability. A two‐step sub‐optimal power allocation scheme is proposed to address the impact of outdated CSI. In the first step, the total transmission power that can be used within one block is determined according to the summation of the channel gains of all the channels. In the second step, the total transmission power is allocated among all the channels. The proposed power control scheme is less sensitive to the feedback delay. Compared to the optimal power allocation scheme designed for the perfect CSI scenario, it has lower computational complexity while achieving comparable capacity. Copyright © 2010 John Wiley & Sons, Ltd.     

Resource allocation in MIMO‐OFDM‐based cooperative cognitive radio networks: optimal and suboptimal low complexity approaches

The problem of resources allocation in multiple‐input multiple‐output‐orthogonal frequency division multiplexing based cooperative cognitive radio networks is considered, in this paper. The cooperation strategy between the secondary users is decode‐and‐forward (DF) strategy. In order to obtain an optimal subcarrier pairing, relay selection and power allocation in the system, the dual decomposition technique is recruited. The optimal resource allocation is realized under the individual power constraints in source and relays so that the sum rate is maximized while the interference induced to the primary system is kept below a pre‐specified interference temperature limit. Moreover, because of the high computational complexity of the optimal approach, a suboptimal algorithm is further proposed. The jointly allocation of the resources in suboptimal algorithm is carried out taking into account the channel qualities, the DF cooperation strategy, the interference induced to the primary system and the individual power budgets. The performance of the different approaches and the impact of the constraint values and deploying multiple antennas at users are discussed through the numerical simulation results. Copyright © 2014 John Wiley & Sons, Ltd.     

Resource allocation algorithm in LTE uplink SC-FDMA system for time-varying channel with imperfect channel state information

In long term evolution (LTE) uplink single carrier frequency division multiple access (SC-FDMA) system, the restriction that multiple resource blocks (RBs) allocated to a user should be adjacent, makes the resource allocation problem hard to solve. Moreover, with the practical constraint that perfect channel state information (CSI) cannot be obtained in time-varying channel, the resource allocation problem will become more difficult. In this paper, an efficient resource allocation algorithm is proposed in LTE uplink SC-FDMA system with imperfect CSI assumption. Firstly, the resource allocation problem is formulated as a mixed integer programming problem. Then an efficient algorithm based on discrete stochastic optimization is proposed to solve the problem. Finally, simulation results show that the proposed algorithm has desirable system performance.     

How much time is needed for wideband spectrum sensing?

In this paper, we consider a wideband cognitive radio network (CRN) which can simultaneously sense multiple narrowband channels and thus aggregate the perceived available channels for transmission. We study the problem of designing the optimal spectrum sensing time and power allocation schemes so as to maximize the average achievable throughput of the CRN subject to the constraints of probability of detection and the total transmit power. The optimal sensing time and power allocation strategies are developed under two different total power constraints, namely, instantaneous power constraint and average power constraint. Finally, numerical results show that, under both cases, for a CRN with three 6MHz channels, if the frame duration is 100ms and the target probability of detection is 90% for the worst case signal-to-noise ratio of primary users being ?12dB, ?15dB and ?20dB, respectively, the optimal sensing time is around 6ms and it is almost insensitive to the total transmit power.     

On the relay selection for cooperative wireless networks with physical-layer network coding

In this paper, we investigate a large cooperative wireless network with relay nodes, in which cooperation is enabled through physical-layer network coding (PLNC). Specifically, we study the impact of the relay selection on the network capacity with power constraints in two scenarios. First, we consider the basic PLNC model (a.k.a., the ARB model), in which one pair of source nodes (A,?B) exchange messages via a selected relay node (R). Given the power constraint, we derive the optimal relay selection and power allocation that maximize the sum capacity, defined as the summation of the capacity for two source-destination channels. Based on results obtained above, we then consider a more general scenario with multiple pairs of source nodes. Assuming the constant power constraint, we derive the upper bound of the minimal sum capacity of any source pair. The optimal power allocation among multiple source pairs is also derived. To validate these theoretical results, we also provide two relay selection strategies: a modified optimal relay assignment strategy and a novel middle point strategy for maximizing the minimal sum capacity of any source pair.     

Opportunistic file transfer over a fading channel under energy and delay constraints

We consider transmission control (rate and power) strategies for transferring a fixed-size file (finite number of bits) over fading channels under constraints on both transmit energy and transmission delay. The goal is to maximize the probability of successfully transferring the entire file over a time-varying wireless channel modeled as a finite-state Markov process. We study two implementations regarding the delay constraints: an average delay constraint and a strict delay constraint. We also investigate the performance degradation caused by the imperfect (delayed or erroneous) channel knowledge. The resulting optimal policies are shown to be a function of the channel-state information (CSI), the residual battery energy, and the number of residual information bits in the transmit buffer. It is observed that the probability of successful file transfer increases significantly when the CSI is exploited opportunistically. When the perfect instantaneous CSI is available at the transmitter, the faster channel variations increase the success probability under delay constraints. In addition, when considering the power expenditure in the pilot for channel estimation, the optimal policy shows that the transmitter should use the pilot only if there is sufficient energy left for packet transfer; otherwise, a channel-independent policy should be used.