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。     

Tradeoff between energy efficiency and spectral efficiency in a delay constrained wireless system

Because of the inevitable trend of green networking, energy efficiency (EE) is quickly becoming one of the key performance metrics to evaluate wireless communication systems, together with spectrum efficiency (SE) and quality of service (QoS) that have been traditionally used. This paper studies the fundamental tradeoff between EE and SE in the presence of statistical QoS requirements in wireless transmission systems. Earlier studies have shown that the performance with QoS requirements in the wireless transmission can be measured through effective capacity, which can capture the physical layer fading channel characteristics in the link layer QoS requirements, such as delay and data rate. Under this context, SE is defined as effective capacity per unit frequency bandwidth, and EE is defined as energy consumed per effective capacity bit. Both circuit power and transmission power are considered in the energy model, based on which we derive the quasi‐convex generalized EE formulation. To exploit the tradeoff between EE and SE with QoS considerations, we propose a generic close‐form approximation for EE–SE formulation by employing a curve fitting approach. The impacts of QoS and circuit power consumption on EE–SE tradeoff are respectively analyzed. QoS requirement and circuit power consumption affect the EE–SE tradeoff differently. In the low‐SNR regime, circuit power shows more impact on the EE–SE tradeoff, whereas QoS impacts EE–SE tradeoff more in the high‐SNR regime. Copyright © 2014 John Wiley & Sons, Ltd.     

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-Spectral-Efficiency Tradeoff in Interference-Limited Wireless Networks

Spectral efficiency (SE) is an important metric in traditional wireless network design. However, as the development of high-data rate services and rapid increase of energy consumption, energy efficiency (EE) has received more and more attention. In this paper, we investigate the EE–SE tradeoff problem in interference-limited wireless networks. Different from previous researches, we try to optimize EE and SE simultaneously. Firstly, the problem is formulated as a multi-objective optimization problem (MOP), with the constraint of transmit power limit. Then, we convert the MOP to a single-objective optimization problem by the weighted linear sum method. We present an algorithm utilizing difference between two convex functions programming (DCP) to handle with SE optimization problem (SD). EE optimization problem can be solved by an algorithm (EFD) consists of fractional programming embedded with DCP. While for EE–SE tradeoff problem, a particle swarm optimization algorithm is proposed (ESTP) to deal with it. Simulation results validate that the proposed algorithm can efficiently balance EE and SE by adjusting the value of weighted coefficient, which could be used to design a flexible energy efficient network in the future.

     

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.     

Energy and spectral efficiency trade‐off for the downlink OFDM‐distributed antenna systems

This paper investigates an energy efficient optimization scheme for the downlink multiuser OFDM‐distributed antenna systems. We adopt a multicriteria optimization method to offer a systematic study on the relationship between spectral efficiency (SE) and energy efficiency (EE). First, we transform the energy efficient optimization problem with high complexity into a simpler downlink multiuser OFDM problem. Then, using the weighted sum method in multicriteria optimization, an optimal energy efficient scheme is presented to allocate the available power to balance the trade‐off between SE and EE efficiently. Simulation results demonstrate that the energy efficient scheme is effective, and there existed a trade‐off between SE and EE in the downlink multiuser OFDM‐distributed antenna systems. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Enhancing the spectral efficiency and energy efficiency of underwater channel communication by optimal cooperative spectrum sensing using hybrid optimization

Underwater wireless sensor networks (UWSNs) contain quite a lot of components such as vehicles and sensors that are deployed in a specific acoustic area to perform collaborative monitoring and data collection errands. These networks are adopted interactively between diverse nodes and ground‐based stations. Currently, UWSNs face problems and challenges that pertain to limited bandwidth, media access control, high propagation delay, 3D topology, spectrum sensing, resource utilization, routing, and power constraints. This proposal deals with the intelligent spectrum sensing in underwater cognitive sonar communication networks (CSCN). Here, the improved performance of spectrum sensing in underwater communication is attained by optimizing the cooperative spectrum sensing and data transmission. The parameters of system like subchannel allocation and transmission power is optimized by a new hybrid meta‐heuristic algorithm by integrating the concepts of deer hunting optimization algorithm (DHOA) and lion algorithm (LA) termed as lion‐enabled DHOA (L‐DHOA). The main intention of optimizing these parameters is to maximize the spectrum efficiency (SE) and energy efficiency (EE) of the underwater channel communication system. From the analysis, with respect to convergence rate, minimum detection probability, and local sensing time, it is proved that the novel hybrid optimization algorithm keeps a great role in making the trade‐off between the SE and EE in underwater channel modeling.     

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.     

Closed Form Expressions for Average Capacity and Symbol Error Rates Under Different Diversity Techniques Over EGK Fading Under Interference

To achieve a tradeoff between spectral efficiency (SE) and energy efficiency (EE) experiences, we design an offloading mechanism to maximize the sum of weighted logarithmic utilities with respect to SE and EE for heterogeneous cellular networks, where the weighting parameters are used for adjusting the SE–EE experiences. Unlike the most existing offloading mechanisms that often try to find a tradeoff between SE and EC (energy consumption), we concentrate on a tradeoff between SE–EE experiences in our mechanism. That is to say, our mechanism directly optimizes EE and is weighted in favour of SE–EE fairness. To solve the finally formulated problem in a mixed-integer and nonlinear form, we firstly make some relaxation for the optimization objective to obtain its an upper bound. Then, we perform a decoupling operation to achieve a decomposable form of dual problem. Finally, we develop a feasible algorithm that can be well implemented in a distributed manner. Numerical results show that the designed mechanism can definitely reach a tradeoff between SE–EE experiences.

     

Energy efficient power allocation in MIMO relaying systems with the MRT precoding

Multiple-input multiple-output (MIMO) systems perform well from the energy efficiency (EE) and the spectral efficiency (SE) points of view in fifth generation (5G) communication systems. This paper considers the operation of a MIMO system with a relay. The optimization problem relates to the EE maximization. This problem has two types of limitations, which provide a maximum transmission power and a minimum data rate for users. The encountered objective function is in a fractional form and thus it is a non-convex function. Besides, the problem is constrained. We utilize a lower bound analysis for the data rates, some properties of the linear programming, and the maximum ratio transmission (MRT) precoding scheme to obtain a convex objective function. Using the Lagrange dual function, we obliterate the constraints of the problem and then it is easy to solve. To improve system performance, users are divided into two groups based on their channel gains, and the maximum transmission power is reasonably divided between them. Two iterative algorithms are proposed to solve the optimization problem numerically, and finally we investigate performance of the proposed method.     

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.     

Energy efficiency optimization of one-way and two-way DF relaying considering circuit power

In this paper, the energy efficiency (EE) of a decode and forward (DF) relay system is studied, where two sources communicate through a half-duplex relay node in one-way and two-way relaying strategies. Both the circuitry power and the transmission power of all nodes are taken into consideration. In addition, three different coding schemes for two-way DF relaying strategy with two phases and two-way DF relaying with three phases are considered. The aim is to maximize the EE of the system for a constant spectral efficiency (SE). For this purpose, the transmission time and the transmission power of each node are optimized. Simulations are used to compare the EE–SE curve of different DF strategies with one-way and two-way amplify and forward (AF) strategies and direct transmission (DT), to find the best energy efficient strategy in different SE conditions. Analytical and simulation results demonstrate that in low SE conditions, DF relaying strategies are more energy efficient compared to that of AF strategies and DT. However, in high SE conditions, the EE of two-way AF relaying and DT strategy outperform some of the DF relaying strategies. In simulations, the impact of different circuitry power and different channel conditions on the EE–SE curves are also investigated.     

Robust energy efficiency power allocation for relay-assisted uplink cognitive radio networks

In this paper, we investigate a worst-case robust power allocation scheme to improve energy efficiency (EE) for an amply-and-forward relaying uplink underlay OFDM cognitive radio system with imperfect channel situation information about the channel between primary user (PU) and secondary user (SU) and the channel between SU and corresponding relay. Specifically, a max–min problem is formulated to transform the original optimization problem into maximum EE on minimum throughout channel, and an epigraph problem is introduced to obtain analytical expressions of objective power allocation. Simulation results show that the proposed EE power allocation scheme is valid and effective in EE and robustness.     

Energy efficiency optimization algorithm for heterogeneous NOMA network based on imperfect CSI

In order to improve the suppression capability of parametric perturbation and energy efficiency (EE) of heterogeneous networks (HetNets),a robust resource allocation algorithm was proposed to maximize system EE for reducing cross-tier interference power in non-orthogonal multiple access (NOMA) based HetNets.Firstly,the resource optimization problem was formulated as a mixed integer and nonlinear programming one under the constraints of the interference power of macrocell users,maximum transmit power of small cell base station (BS),resource block assignment and the quality of service (QoS) requirement of each small cell user.Then,based on ellipsoid bounded channel uncertainty models,the original problem was converted into the equivalent convex optimization problem by using the convex relaxation method,Dinkelbach method and the successive convex approximation (SCA) method.The analytical solutions were obtained by using the Lagrangian dual approach.Simulation results verifiy that the proposed algorithm had better EE and robustness by comparing it with the existing algorithm under perfect channel state information.     

On the Ergodic Capacity and Energy Efficiency for Fading MIMO NOMA Systems

Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access techniques for 5G networks due to its superior spectral efficiency (SE). Previous research mainly focus on the design to improve the SE performance with instantaneous channel state information (CSI). In this paper, we consider the fading MIMO channels with only statistical CSI at the transmitter, and explore the potential gains of MIMO NOMA scheme in terms of both ergodic capacity and energy efficiency (EE). The ergodic capacity maximization problem is first studied for the fading multiple-input multiple-output (MIMO) NOMA systems. We derive the optimal input covariance structure and propose both optimal and low complexity suboptimal power allocation schemes to maximize the ergodic capacity of MIMO NOMA system. For the EE maximization, the optimization problem is formulated to maximize the system EE (defined by ergodic capacity under unit power consumption) under the total transmit power constraint and the minimum rate constraint of the weak user. By transforming the EE maximization problem into an equivalent one-dimensional optimization problem, the optimal power allocation for EE design is proposed. To further reduce the computation complexity, a near-optimal solution based on golden section search and suboptimal closed form solution are proposed as well. Numerical results show that the proposed NOMA schemes significantly outperform the traditional orthogonal multiple access scheme with traditional orthogonal multiple access transmission in terms of both SE and EE.     

Optimal resource allocation for energy efficiency in coordinated multicell OFDMA networks

Because energy efficiency (EE) is inevitable in future wireless cellular networks, in this paper, we focus on improving the number of bits delivered to users for each unit energy consumption in the downlink of orthogonal frequency‐division multiple access cellular networks with base stations (BSs) coordination. Specifically, each BS shares the channel qualities of users with others and jointly choose the set of co‐channel users and the transmit power allocated to maximize the EE of the system subject to the transmit power ceiling of each BS and minimum required data rate. We formulate the problem as a nonlinear fractional optimization problem, using nonlinear fractional programming, the original hard‐to‐solve problem is transferred to a new one that has the same optimal solution and is easier to solve, this enables two iterative algorithms that achieve nearly the same maximum EE. Numerical results are provided to show the convergence and superiority of the two proposed. Copyright © 2014 John Wiley & Sons, Ltd.     

Energy efficient power allocation strategy for downlink MU-MIMO with massive antennas

With the increasing energy consumption, energy efficiency （EE） has been considered as an important metric for wireless communication networks as spectrum efficiency （SE）. In this paper, EE optimization problem for downlink multi-user multiple-input multiple-output （MU-MIMO） system with massive antennas is investigated. According to the convex optimization theory, there exists a unique globally optimal power allocation achieving the optimal EE, and the closed-form of the optimal EE only related to channel state information is derived analytically. Then both the approximate and accurate power allocation algorithms with different complexity are proposed to achieve the optimal EE. Simulation results show that the optimal EE obtained by the approximate algorithm coincides to that achieved by the accurate algorithm within the controllable error limitation, and these proposed algorithms perform better than the existing equal power allocation algorithm. The optimal EE and corresponding SE increase with the number of antennas at base station, which is promising for the next generation wireless communication networks.     

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.     

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.