Energy spectral efficiency tradeoff in downlink OFDMA network

Spectral efficiency (SE) is an important metric in traditional wireless network design. However, as the development of high‐data rate services and rapidly increase of energy consumption, energy efficiency (EE) has received more and more attention. In this paper, we investigate the EE–SE tradeoff in downlink OFDMA network. Different from previous researches, we try to optimize EE and SE simultaneously. First, the problem is formulated as a multiobjective optimization problem (MOP), and its Pareto optimal set is characterized. Then, we convert the MOP to a single‐objective optimization problem (SOP) by the weighted linear sum method and show that it is neither quasi‐convex nor quasi‐concave. After that, a novel algorithm using particle swarm optimization is proposed to solve the SOP. Simulation results validate that the proposed algorithm can efficiently reduce total transmit power and improve EE, although the cost is sacrificing some SE, which could be used to design an flexible energy efficient network in the future.Copyright © 2014 John Wiley & Sons, Ltd.     

Energy‐Efficiency Power Allocation for Cognitive Radio MIMO‐OFDM Systems

This paper studies energy‐efficiency (EE) power allocation for cognitive radio MIMO‐OFDM systems. Our aim is to minimize energy efficiency, measured by “Joule per bit” metric, while maintaining the minimal rate requirement of a secondary user under a total power constraint and mutual interference power constraints. However, since the formulated EE problem in this paper is non‐convex, it is difficult to solve directly in general. To make it solvable, firstly we transform the original problem into an equivalent convex optimization problem via fractional programming. Then, the equivalent convex optimization problem is solved by a sequential quadratic programming algorithm. Finally, a new iterative energy‐ efficiency power allocation algorithm is presented. Numerical results show that the proposed method can obtain better EE performance than the maximizing capacity algorithm.     

基于能量效率的分布式星群下行链路功率分配方法研究

针对多波束卫星通信系统星上资源稀缺和能量利用效率不高的问题,本文提出了分布式星群网络下行链路中兼顾系统功耗和数据速率的功率分配方法,通过合理的资源分配来优化系统的能量效率.首先建立分布式星群功率分配模型,将复杂的分式问题转化为易于求解的减法形式问题,然后基于凸优化理论,提出功耗-数据速率权衡功率分配算法,并讨论了能量效率（energy efficiency）与频谱效率（spectral efficiency）之间的权衡关系.仿真结果验证了提出算法的有效性和EE-SE权衡关系,并分析了电路功耗对系统性能的影响.     

Power allocation scheme based on sum capacity maximization for signal‐to‐leakage‐and‐noise ratio precoded multiuser multiple‐input single‐output downlink

This paper proposes a power allocation scheme to maximize the sum capacity of all users for signal‐to‐leakage‐and‐noise ratio (SLNR) precoded multiuser multiple‐input single‐output downlink. The designed scheme tries to explore the effect of the power allocation for the SLNR precoded multiuser multiple‐input single‐output system on sum capacity performance. This power allocation problem can be formulated as an optimization problem. With high signal‐to‐interference‐plus‐noise ratio assumption, it can be converted into a convex optimization problem through the geometric programming and hence can be solved efficiently. Because the assumption of high signal‐to‐interference‐plus‐noise ratio cannot be always satisfied in practice, we design a globally optimal solution algorithm based on a combination of branch and bound framework and convex relaxation techniques. Theoretically, the proposed scheme can provide optimal power allocation in sum capacity maximization. Then, we further propose a judgement‐decision algorithm to achieve a trade‐off between the optimality and computational complexity. The simulation results also show that, with the proposed scheme, the sum capacity of all the users can be improved compared with three existing power allocation schemes. Meanwhile, some meaningful conclusions about the effect of the further power allocation based on the SLNR precoding have been also acquired. The performance improvement of the maximum sum capacity power allocation scheme relates to the transmit antenna number and embodies different variation trends in allusion to the different equipped transmit antenna number as the signal‐to‐noise ratio (SNR) changes.Copyright © 2013 John Wiley & Sons, Ltd.     

Energy efficiency and spectral efficiency tradeoff in downlink OFDMA systems with imperfect CSI

In this paper, we investigate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in downlink orthogonal frequency division multiplexing access (OFDMA) systems, whilst considering the channel estimation cost and the corresponding effect of imperfect channel state information (CSI) on SE and EE. The problem is formulated as a multi-objective optimization to determine the optimal pilot transmission power, data transmission power and subcarrier assignment, and then transformed into a single-objective optimization problem, which is a non-convex mixed-integer nonlinear programming (NCMINP) and NP-hard. To address it, we propose an efficient algorithm by adopting alternating optimization and convex optimization methods in lower power region as well as approximate conversion and branch-and-bound methods in high power region. Simulation results analyze and validate the performance of EE-SE tradeoff.     

Low‐complexity energy efficient power allocation scheme for DAS with maximum power constraint

In this paper, a low‐complexity optimal power allocation (PA) scheme is developed to maximize energy efficiency (EE) in a distributed antenna system (DAS) under maximum power constraint and target bit error rate (BER) requirement. Composite Rayleigh fading, multiple receive antennas, and dynamic circuit power consumption are all considered in the system. Unlike conventional schemes, the presented scheme provides a closed‐form expression of PA. Firstly, the optimization problem is formulated according to the definition of EE. Using the Karush‐Kuhn‐Tucker conditions, a general form of the optimal PA, in which the number of active antennas and corresponding power allocation are required only, is then proposed. With this general form, an effective algorithm is presented to yield the closed‐form PA. The proposed scheme can be applied to the system with static circuit power consumption and/or without target BER constraint to obtain optimal PA. Simulation results corroborate the effectiveness of the developed scheme, and the scheme can achieve the same EE performance as the existing optimal schemes with lower complexity. Moreover, the distributed antenna system with multiple receive antennas has higher EE than that with single receive antenna.     

能量有效的认知多小区协同波束赋形算法

针对认知多小区多用户下行传输链路,提出了一种基于能量效率最大化准则的协同波束赋形优化方法。该方法采用迫零消除小区内用户间干扰,在保证用户最小速率需求及认知干扰约束的同时,实现了能量效率和频谱效率的同步改善。为了分布式求解优化问题,通过约束泄露干扰并利用半定松弛,将其转换为凸问题,在此基础上,采用部分对偶分解方法将多小区联合优化问题分解为一组单小区优化问题,从而实现了分布式求解。仿真结果表明,该方法不仅实现了能量效率和频谱效率的有效折中,而且达到了集中式算法的性能。     

Distributed energy efficient beamforming algorithm for multicell multiuser downlink system

A distributed energy efficient beamforming algorithm was studied for multicell multiuser downlink communication system.Firstly,the energy efficient optimization problem was first considered as the maximization of the ratio between the system sum rate and the system power consumption.The fractional programming optimization target was then transformed into a subtractive form via using the fractional programming theorem.Secondly,the problem was decomposed into some subproblems that can be solved respectively by introducing the concept of the interference temperature in cognitive radio networks.Finally,an effective distributed energy efficient beamforming algorithm was proposed by exploiting the Lagrangian duality theorem and optimization theorem.Compared to the classical energy efficient optimization algorithm,the proposed algorithm can achieve an obvious energy efficiency performance gain.     

QoS‐Guaranteed Multiuser Scheduling in MIMO Broadcast Channels

This paper proposes a new multiuser scheduling algorithm that can simultaneously support a variety of different quality‐of‐service (QoS) user groups while satisfying fairness among users in the same QoS group in MIMO broadcast channels. Toward this goal, the proposed algorithm consists of two parts: a QoS‐aware fair (QF) scheduling within a QoS group and an antenna trade‐off scheme between different QoS groups. The proposed QF scheduling algorithm finds a user set from a certain QoS group which can satisfy the fairness among users in terms of throughput or delay. The antenna trade‐off scheme can minimize the QoS violations of a higher priority user group by trading off the number of transmit antennas allocated to different QoS groups. Numerical results demonstrate that the proposed QF scheduling method satisfies different types of fairness among users and can adjust the degree of fairness among them. The antenna trade‐off scheme combined with QF scheduling can improve the probability of QoS‐guaranteed transmission when supporting different QoS groups.     

Energy-efficient power allocation scheme for distributed MISO system with transmit correlation

The energy efficiency (EE) of distributed multiple-input single-output (MISO) system is investigated in spatially-correlated Rayleigh channels, where large-scale fading including the path loss and the shadow fading is considered. The target is to maximize the EE which is defined as the ratio of the transmission rate to the total power consumed by the system subject to the maximum transmit power of each remote antenna unit (RAU) constraint. The EE optimization can be formulated as a nonlinear fractional programming problem. An optimal power allocation (PA) scheme for maximizing the EE is proposed. With this scheme, an iterative algorithm using Dinkelbach method is presented. To avoid iterative calculation, a low-complexity simplified PA scheme is developed based on the good channel information for antenna selection; it can provide a computational efficient method to acquire the optimal numbers of active RAUs. Therefore, the multidimensional optimization problem is converted to a single-dimensional optimization problem. As a result, the closed-form PA is attained. The simulation results validate the effectiveness of the proposed two schemes. The results indicate that these two schemes can achieve very similar performance, and the simplified scheme has lower complexity because no iteration is required.     

Per‐antenna power minimization in symbol‐level precoding for the multibeam satellite downlink

This paper addresses the problem of multiuser interference in the forward downlink channel of a multibeam satellite system. A symbol‐level precoding scheme is considered, to exploit the multiuser interference and transform it into useful power at the receiver side, through a joint utilization of the data information and the channel state information. In this context, a per‐antenna power minimization scheme is proposed, under quality‐of‐service constraints, for multilevel modulation schemes. The consideration of the power limitations individually for each transmitting radio frequency chain is a central aspect of this work, and it allows to deal with systems using separate per‐antenna amplifiers. Moreover, this feature is also particularly relevant for systems suffering nonlinear effects of the channel. This is the case of satellite systems, where the nonlinear amplifiers should be properly driven to reduce the detrimental saturation effect. In the proposed scheme, the transmitted signals are designed to reduce the power peaks, while guaranteeing some specific target signal‐to‐noise ratios at the receivers. Numerical results are presented to show the effectiveness of the proposed scheme, which is compared both with the state of the art in symbol‐level precoding and with the conventional minimum mean square error precoding approach.     

多无人机协作的认知通信网络中能/谱效折中优化

在无人机（Unmanned Aerial Vehicle,UAV）认知通信网络中,其能量受限和通信高吞吐量问题备受关注。然而,能量效率（Energy Efficiency,EE）的提升可能会导致频谱效率（Spectrum Efficiency,SE）的下降。针对此问题,对UAV协作认知通信网络中EE和SE的折中优化进行了研究。首先,进行了感知时间、UAV通信的发射功率和判决门限各自对SE与EE两者的优化;其次,通过二分法求解使得EE和SE最大化的感知时间值,并通过穷尽搜索法分别求解感知时间、UAV通信的发射功率和判决门限对EE和SE折中优化问题的最优参数值。在此基础上,提出一种联合参数迭代优化算法,求解EE和SE的折中优化问题。仿真实验表明,SE和EE之间存在折中的权衡,并验证了所提优化方案的有效性。     

On proportional fairness of uplink spectral efficiency in cell‐free massive MIMO systems

This paper is concerned with the proportional fairness (PF) of the spectral efficiency (SE) maximization of uplinks in a cell‐free (CF) massive multiple‐input multiple‐output (MIMO) system in which a large number of single‐antenna access points (APs) connected to a central processing unit (CPU) serve many single‐antenna users. To detect the user signals, the APs use matched filters based on the local channel state information while the CPU deploys receiver filters based on knowledge of channel statistics. We devise the maximization problem of the SE PF, which maximizes the sum of the logarithm of the achievable user rates, as a jointly nonconvex optimization problem of receiver filter coefficients and user power allocation subject to user power constraints. To handle the challenges associated with the nonconvexity of the formulated design problem, we develop an iterative algorithm by alternatively finding optimal filter coefficients at the CPU and transmit powers at the users. While the filter coefficient design is formulated as a generalized eigenvalue problem, the power allocation problem is addressed by a gradient projection (GP) approach. Simulation results show that the SE PF maximization not only offers approximately the achievable sum rates as compared to the sum‐rate maximization but also provides an improved trade‐off between the user rate fairness and the achievable sum rate.     

Energy‐Efficient Power Allocation for Cognitive Radio Networks with Joint Overlay and Underlay Spectrum Access Mechanism

Traditional designs of cognitive radio (CR) focus on maximizing system throughput. In this paper, we study the joint overlay and underlay power allocation problem for orthogonal frequency‐division multiple access–based CR. Instead of maximizing system throughput, we aim to maximize system energy efficiency (EE), measured by a “bit per Joule” metric, while maintaining the minimal rate requirement of a given CR system, under the total power constraint of a secondary user and interference constraints of primary users. The formulated energy‐efficient power allocation (EEPA) problem is nonconvex; to make it solvable, we first transform the original problem into a convex optimization problem via fractional programming, and then the Lagrange dual decomposition method is used to solve the equivalent convex optimization problem. Finally, an optimal EEPA allocation scheme is proposed. Numerical results show that the proposed method can achieve better EE performance.     

An energy-efficient power allocation scheme for millimeter-wave MIMO-NOMA systems

There are many challenges in fifth generation (5G) telecommunication systems, due to the increasing demands and applications. The most important of which are need to have higher energy efficiency (EE) and spectral efficiency (SE). They are critical in the practical multiple-input multiple-output (MIMO) telecommunication systems. Non-orthogonal multiple access (NOMA) methods and millimeter-waves can be used in conjunction with MIMO systems to improve their EE and SE performance. In this paper, we investigate the application of NOMA and mm-Wave transmission in the downlink of MIMO systems. Then, we formulate the optimization problem for users in MIMO-NOMA systems to maximize the EE that is subject to minimum data rate to satisfy required quality of service (QoS) and maximum transmission power. To achieve the optimal power allocation for users, we reach a problem for the EE maximization that is non-convex and solution of the optimization problem is not trivial. We exploit a lower bound of the data rate and the Lagrange dual function to convert it to a convex and unconstrained problem, which is easy to solve. In the next step, we derive a relation for determining the optimal power allocation of users. In addition, a numerical algorithm is presented that can be used to solve the problem. According to the simulation results of the proposed algorithm, our method performs better and provides higher EE than both orthogonal multiple access and equal power allocation schemes.     

Spectral efficiency and energy efficiency of distributed antenna systems with virtual cells

In this paper, we consider user centric virtual cells model in distributed antenna systems (DAS). We investigate different power allocation optimization problems with interferences in DAS with and without user centric virtual cells model, respectively. The first objective problem is maximizing spectral efficiency (SE) of the DAS with user centric virtual cells model under the constraints of the minimum SE requirements of each user equipment (UE), maximum transmit power of each remote access unit (RAU). We firstly transform this non-convex objective function into a difference of convex functions (D.C.) problem, and then we obtain the optimal solutions by using the concave-convex procedure (CCCP) algorithm. The second objective problem is maximizing energy efficiency (EE) of the DAS with user centric virtual cells model under the same constraints as the first objective problem. Firstly, we exploit fractional programming theory to obtain the equivalent objective function of the second problem with subtract form, and then transform it into a D.C. problem and use CCCP algorithm to obtain the optimal power allocation. In each part, we propose the corresponding optimal power allocation algorithm and also use similar method to obtain optimal solutions of the same optimization problems in DAS without using user centric virtual cells model. Simulation results are provided to demonstrate the effectiveness of the DAS with user centric virtual cells model, which can significantly improve the SE and the EE of the communication systems.     

Energy efficiency comparison between distributed and co‐located MIMO systems

Energy efficiency (EE) is becoming more and more important in future wireless communications because of limited battery power in mobile terminals. In this paper, we compare EE of the distributed MIMO (D‐MIMO) and co‐located MIMO (C‐MIMO) in uplink systems. Taking into account both circuit and transmit power, we derive an analytical expression for EE of D‐MIMO and C‐MIMO systems in a composite Rayleigh‐lognormal channel. What is more, an optimization algorithm is proposed to get the optimal EE values while satisfying given spectral efficiency requirement for both D‐MIMO and C‐MIMO systems. Simulation results show that D‐MIMO systems are more energy effective than C‐MIMO systems when considering the realistic systems, and the optimal EE can be obtained by the proposed algorithm while satisfying given spectral efficiency requirement. Copyright © 2012 John Wiley & Sons, Ltd.     

基于天线选择技术的大规模下行MU-MIMO系统能效分析

为了提高大规模多用户多输入多输出(MU-MIMO)下行系统的能效,提出了一种基于发送天线选择技术的能效优化机制。首先建立了同时考虑发送功率与电路功耗的新的系统功耗模型,并基于该模型,分析了基站配置天线数目与所有接收终端用户数目对系统总功耗及能效的影响。然后通过理论推导得到了系统能效最优时的最优天线选择数目,并与使用全部天线时的系统能效进行比较。仿真结果表明,所提出的发送天线选择机制通过优化激活部分基站天线能够明显提高系统能效。在用户数为10、发送功率分别为40 W和10 W时,与使用全部天线相比,天线选择技术能够分别使得系统能效获得大约12%和78%的性能增益。     

Traffic‐aware downlink power allocation in multiuser OFDM system

Multiuser orthogonal frequency division multiplexing (OFDM) is a promising technology to achieve high uplink/downlink (DL) capacities in the next generation broadband wireless networks such as WiMAX (Worldwide Interoperability for Microwave Access). In this paper, we investigate the DL adaptive power allocation (APA) in multiuser OFDM system from the perspective of cross‐layer design. Specifically, we formulate APA as an optimization problem with the traffic profile of each user asit a priori knowledge. To solve the optimization problem, we develop a fairness‐constrained optimal prioritized effective throughput (PET) strategy and the corresponding iterative algorithms, aiming at balancing the prioritized effective throughput and the linear or logarithmic user satisfaction‐based fairness. Simulation results show that our proposed APA optimization approach can achieve satisfying performance. Copyright © 2011 John Wiley & Sons, Ltd.     

Power allocation scheme for maximizing spectrum efficiency and energy efficiency tradeoff for multi-cluster NOMA system

In this paper, a power allocation to maximize tradeoff between spectrum efficiency (SE) and energy efficiency (EE) is considered for the downlink non-orthogonal multiple access (NOMA) system with arbitrarily clusters and arbitrarily users, where the subcarriers of clusters are mutually orthogonal to each other. Specifically, an optimization problem of maximizing SE-EE tradeoff is formulated by optimizing power allocation among users under the constraints of user rate requirements. Then, the optimization problem is decomposed into a group of sub-problems with the aim of maximizing SE-EE tradeoff for each cluster, which is solved by using bisection method and monotonicity of function. Finally, the power allocation optimization problem among users is transformed into that between clusters, and a two steps inter-cluster power allocation algorithm is developed to solve this problem. Simulation results show that SE-EE tradeoff of the proposed scheme is better than that of the existing schemes.