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.     

Energy‐efficient resource allocation in D2D communications for energy harvesting–enabled NOMA‐based cellular networks

In this paper, we propose an energy‐efficient power control and harvesting time scheduling scheme for resource allocation of the subchannels in a nonorthogonal multiple access (NOMA)–based device‐to‐device (D2D) communications in cellular networks. In these networks, D2D users can communicate by sharing the radio resources assigned to cellular users (CUs). Device‐to‐device users harvest energy from the base station (BS) in the downlink and transmit information to their receivers. Using NOMA, more than one user can access the same frequency‐time resource simultaneously, and the signals of the multiusers can be separated successfully using successive interference cancellation (SIC). In fact, NOMA, unlike orthogonal multiple access (OMA) methods, allows sharing the same frequency resources at the same time by implementing adaptive power allocation. Our aim is to maximize the energy efficiency of the D2D pairs, which is the ratio of the achievable throughput of the D2D pairs to their energy consumption by allocating the proper subchannel of each cell to each device user equipment (DUE), managing their transmission power, and setting the harvesting and transmission time. The constraints of the problem are the quality of service of the CUs, minimum required throughput of the subchannels, and energy harvesting of DUEs. We formulate the problem and propose a low‐complexity iterative algorithm on the basis of the convex optimization method and Karush‐Kuhn‐Tucker conditions to obtain the optimal solution of the problem. Simulation results validate the performance of our proposed algorithm for different values of the system parameters.     

Semi‐distributed resource management for underlay D2D communication with user's cooperation

Device‐to‐device (D2D) communication is a viable solution proposed by the Third Generation Partnership Project (3GPP) to handle the enormous number of devices and expected data explosion in 5G. It is competent in enhancing the system performances such as increased data rate, reduced delay, and less power consumption while maintaining a low load on the base station (BS). In this paper, channel assignment and power control scheme is proposed for underlay D2D system where one cellular channel is allowed to be shared among multiple D2D pairs. This will lead to enhanced spectral efficiency on the cost of additional interferences introduced among the D2D and cellular users (CUs). Our aim is to maximize the D2D throughput without degrading the performance of existing CU that is sharing the channel with D2D. This is achieved by maintaining a threshold signal‐to‐interference‐plus‐noise ratio (SINR) for each CU. A centralized channel assignment algorithm based on the well‐known two‐sided preference Gale‐Shapley algorithm is proposed, named as RAbaGS‐HR. Further, suboptimal distributed power control (DPC) algorithms are proposed for both uplink and downlink D2D. The novelty of the work lies in the facts that a channel is shared among multiple D2D users and the optimal power is calculated for all the users sharing the same channel under the full consideration of all kinds of interferences unlike most of the existing work that either assumed the fixed CU power or ignored the interferences among the D2D users. Numerical results show the efficacy of the proposed algorithms in terms of significant gain in throughput with a very low computational cost. In addition to this, the energy efficiency (EE) is also analyzed for different D2D user density, with respect to average circuit power consumption and D2D maximum transmit power.     

Energy efficient radio resource management for heterogeneous wireless network using CoMP

The coordinated multi point (CoMP) transmission technique is considered a key feature in future wireless network to improve both cell edge users throughput by exploiting interference. However, to provide CoMP transmission several BSs need to be active, which eventually increases network energy consumption. The simultaneous active multiple BSs with different transmission characteristics in heterogeneous environment cause interferences on each other. In this paper, we study the energy efficient radio resource management (EE-RRM) scheme for heterogeneous wireless networks to reduce interference. In particular, our aim is to allocate subcarrier power by optimizing EE metric and minimize interference with knowledge of channel state information between BSs and user equipment. The EE-RRM problem is a fractional programming problem. In order to solve, we use Charnes–Cooper transformation technique and transform it into an equivalent concave optimization problem. The numerical results of our work present the effect of different interference, rate and power thresholds on the EE metric.     

Massive MIMO异构网的高能效资源分配

为满足第五代移动通信系统高频谱效率和高能量效率的需求,提出一种工作在不同频段下行两层异构网中的高能量效率资源分配方法,考虑用户数据率需求和基站最大发射功率。天线和传输带宽是影响系统能量效率的关键因素。通过研究宏基站和小基站的天线资源和带宽分配发现:当系统天线数很大时,发射功耗的影响可以忽略不计;给定带宽分配因子时,达到宏基站或微基站最大发射功率的天线分配因子几乎可以达到最高能效;给定天线分配因子时,系统平均总功耗是关于带宽分配因子的下凸函数,存在全局最优带宽分配因子使能效最高。仿真结果表明,与给定带宽和天线资源的异构网和小小区网络相比,所提出的异构网可以显著提高系统能量效率,而且在大量用户、高数据率需求时能效提升更明显。      

Robust resource allocation for NOMA-assisted heterogeneous networks

As a promising technology to improve spectrum efficiency and transmission coverage, Heterogeneous Network (HetNet) has attracted the attention of many scholars in recent years. Additionally, with the introduction of the Non-Orthogonal Multiple Access (NOMA) technology, the NOMA-assisted HetNet cannot only improve the system capacity but also allow more users to utilize the same frequency band resource, which makes the NOMA-assisted HetNet a hot topic. However, traditional resource allocation schemes assume that base stations can exactly estimate direct link gains and cross-tier link gains, which is impractical for practical HetNets due to the impact of channel delays and random perturbation. To further improve energy utilization and system robustness, in this paper, we investigate a robust resource allocation problem to maximize the total Energy Efficiency (EE) of Small-Cell Users (SCUs) in NOMA-assisted HetNets under imperfect channel state information. By considering bounded channel uncertainties, the robust resource optimization problem is formulated as a mixed-integer and nonlinear programming problem under the constraints of the cross-tier interference power of macrocell users, the maximum transmit power of small base station, the Resource Block (RB) assignment, and the quality of service requirement of each SCU. The original problem is converted into an equivalent convex optimization problem by using Dinkelbach's method and the successive convex approximation method. A robust Dinkelbach-based iteration algorithm is designed by jointly optimizing the transmit power and the RB allocation. Simulation results verify that the proposed algorithm has better EE and robustness than the existing algorithms.     

可重构智能表面辅助的非正交多址接入网络鲁棒能量效率资源分配算法

为提高非正交多址接入(NOMA)网络的鲁棒性和系统能效(EE),考虑了不完美信道状态信息,该文提出一种可重构智能表面(RIS)辅助的NOMA网络鲁棒能效最大资源分配算法。考虑用户信干噪比(SINR)中断概率约束、基站的最大发射功率约束以及连续相移约束,建立了一个非线性的能效最大化资源分配模型。用Dinkelbach方法将分式形式的目标函数转换为线性的参数相减的形式,利用S-procedure方法将含有信道不确定性的SINR中断概率约束转换成确定性形式,利用交替优化算法将多变量耦合的非凸优化问题分解成多个凸优化子问题,最后用CVX对分解出的子问题进行求解。仿真结果表明,在EE方面,所提算法比无可重构智能表面(RIS)算法提高了7.4%。在SINR中断概率方面,所提算法比非鲁棒算法降低了85.5%。     

云无线接入网络高能效功率分配和波束成形联合优化算法

针对云无线接入网络(C-RAN)的资源分配问题,该文采用max-min公平准则作为优化准则,以C-RAN用户的能量效率作为优化目标函数,在满足最大发射功率和最小传输速率约束条件下,通过最大化最差链路的能量效率来实现用户发射功率和无线远端射频单元(RRHs)波束成形向量的联合优化。上述优化问题属于非线性、分式规划问题,为了方便求解,首先将原优化问题转化为差分形式的优化问题,然后通过引入变量将差分形式的、非平滑优化问题转化为平滑优化问题。最终,提出一种双层迭代功率分配和波束成形算法。在仿真实验中,将该文算法与传统的非能效资源分配算法和能量效率最大化算法进行了比较,实验结果证明该文算法在改进C-RAN能量效率和提高资源分配公平性方面的有效性。     

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.     

异构无线网络干扰效率最大顽健资源分配算法

针对能效提升、宏用户干扰减小的问题,该文研究了基于干扰效率最大的异构无线网络顽健资源分配算法.首先,考虑宏用户干扰约束、微蜂窝用户速率需求约束和最大发射功率约束,将资源优化问题建模为多变量非线性规划问题.其次,考虑有界信道不确定性模型,利用Dinkelbach辅助变量方法和连续凸近似方法结合对数变换方法,将原分式规划顽健资源分配问题转换为等价的确定性凸优化问题,并利用拉格朗日对偶算法获得解析解.理论分析了计算复杂度和参数不确定性对性能的影响.仿真结果表明该算法具有较好的干扰效率和鲁棒性.     

Energy‐efficient relay deployment in cellular systems using fractional frequency reuse and transmit antenna selection techniques

To cope with the steep surge in mobile traffic, network operators are now expanding their infrastructure for mobile access networks. However, since energy costs and greenhouse gas emissions are a large burden to network operators, they are making great efforts to improve the energy efficiency (EE) of their networks by promising techniques, including relaying and multiple‐input multiple‐output (MIMO). Relaying technique can considerably improve the EE when the interference between base stations (BSs) and relay stations (RSs) is effectively coordinated by an elaborate relay deployment using the fractional frequency reuse (FFR) technique. Also, MIMO techniques improve the radio channel quality through diversity gains, so the system capacity and the EE can be improved. Therefore, a combination of relaying/MIMO techniques can be considered to achieve the higher performance, particularly, if the system complexity and costs of using such techniques are low. Since the transmit antenna selection (TAS), one of MIMO techniques, can provide a sufficient transmit diversity gain and satisfy the requirements for low complexity and cost (thus, practical), the TAS is recommended for use with the relaying technique. In this paper, for an energy‐efficient relay deployment using FFR and TAS techniques, we derive the EE and the resource partitioning according to RS positions and the number of BS antennas by a mathematical analysis. Then, the optimal RS positions according to the number of antennas can be determined by an optimization approach. The numerical and simulation results indicate that the proposed analysis method can efficiently analyze the EE and locate the RSs.     

认知蜂窝网络环境下的上行节能方法研究

针对蜂窝网用户在高速数据传输时能耗过高的问题,基于认知蜂窝网络模型,提出了一种通过合理利用认知网络资源进行多网络并发传输的最大能效传输策略。该策略利用多模终端可以同时接入不同网络进行并发传输的特点,建立用户能效模型,并通过研究并发传输时不同网络可用信道状态、能耗和数据传输速率之间的关系,得出使用户能效最大的认知网络资源使用和数据传输速率分配算法。仿真结果表明,该最大能效策略能够有效提升用户的能效。     

Energy-efficient association mechanism designed for uplink CDMA-based HCNs

To reduce the energy consumption and prolong the battery lifetimes of mobile terminals, the design of energy-efficient association scheme is necessary and meaningful. To this end, we design a type of association mechanism (scheme) to maximize the whole energy efficiency (WEE) for uplink code-division-multiple-access (CDMA)-based heterogeneous cellular networks (HCNs), and formulate it as a WEE maximization problem with users’ SINR (signal-to-interference-plus-noise ratio) constraints. Considering that the finally formulated problem is in a fractional mixed-integer form and hard to tackle, we introduce an energy efficiency (EE) parameter to convert it into a parametric subtractive form. At last, we design two two-layer iterative algorithms for the formulated problem, whose primary difference lies in the treatment of SINR constraints. In general, the outer loop utilizes a bisection method to search the optimal EE parameter, and the inner loop alternately optimizes the association index and transmit power. At last, we give the corresponding convergence analyses for some subalgorithms, and also give some detailed complexity analyses for the whole algorithm. In the simulation, we introduce an existing energy-efficient association mechanism for comparison, and finally investigate the impacts of different network parameters on the association performance.     

On selecting transmission mode for D2D transmitter in underlay cellular network with a multi-antenna base station

The Device-to-Device (D2D) communication underlaying cellular networks is considered in this study. The D2D transmitter in the D2D mode can directly transmit messages to a receiver, but it may interfere with the transmission of another cellular user who shares the same uplink channel. The transmitter can also operate in a cellular mode in which no interference to another cellular user occurs. We propose a mode selection scheme that aims to minimize the transmission power of the D2D transmitter subject to constraints on the minimum required data rate and maximum interference to other cellular users. The proposed scheme is based on bounds for transmission power and is less complex than the optimal scheme. Furthermore, it requires only a few statistics and does not need a fading channel distribution. The performance of the scheme is close to optimum when the number of Base Station (BS) antennas is large, and the mean absolute deviation of the fading terms is small. We verify this with numerical results of the Rician and Rayleigh fading channels by assuming that the BS antennas are independent. The simulation results for the two correlated BS antennas are presented herein.     

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.     

Energy efficiency optimization for HCNs based on small base station transmission power allocation

In the research of green communication, considering the base station (BS) power allocation from the perspective of energy efficiency (EE) is meaningful for heterogeneous cellular networks (HCNs) optimization. The EE of two-tier HCNs was analyzed and a new method for the network EE optimization was proposed by adjusting the small BS transmitting power. First, the HCNs ware modeled by homogeneous Poisson point processes (PPPs), and the coverage probability of BSs in each tier was derived. Second, according to the definition of EE, and the closed-form of EE was given by deriving the total power consumption and total throughput of HCNs respectively. At last, the analytical performance of the EE of HCNs on the small BS transmission power was analyzed, and a small BS power optimization algorithm was proposed to maximize the EE. Simulation results show that, the transmission power of small BS has a significant impact on the EE of HCNs. Furthermore, by optimizing the transmission power of small BS, the EE of HCNs can be improved effectively.     

基于NOMA的无线携能D2D通信鲁棒能效优化算法

针对频谱短缺、基站负荷过高、通信系统功耗较大等问题,考虑不完美的信道状态信息,该文提出一种基于非正交多址接入的无线携能(SWIPT)D2D网络鲁棒能效(EE)最大化资源分配算法(SREA).考虑用户的服务质量约束以及最大发射功率约束,基于随机信道不确定性建立鲁棒能效最大化资源分配模型.利用Dinkelbach和变量替换方法,将原NP-hard问题转换为确定性的凸优化问题,通过拉格朗日对偶理论求得解析解.仿真结果表明,所提算法在保证蜂窝用户通信质量的同时,能够有效提高D2D用户的能效性和鲁棒性能.     

基于NOMA的无线携能D2D通信鲁棒能效优化算法

针对频谱短缺、基站负荷过高、通信系统功耗较大等问题,考虑不完美的信道状态信息,该文提出一种基于非正交多址接入的无线携能(SWIPT)D2D网络鲁棒能效(EE)最大化资源分配算法(SREA)。考虑用户的服务质量约束以及最大发射功率约束,基于随机信道不确定性建立鲁棒能效最大化资源分配模型。利用Dinkelbach和变量替换方法,将原NP-hard问题转换为确定性的凸优化问题,通过拉格朗日对偶理论求得解析解。仿真结果表明,所提算法在保证蜂窝用户通信质量的同时,能够有效提高D2D用户的能效性和鲁棒性能。     

Resource allocation and dynamic power control for D2D communication underlaying uplink multi-cell networks

Underlaying device-to-device (D2D) communication is suggested as a promising technology for the next generation cellular networks (5G), where users in close proximity can transmit directly to one another bypassing the base station. However, when D2D communications underlay cellular networks, the potential gain from resource sharing is highly determined by how the interference is managed. In order to mitigate the resource reuse interference between D2D user equipment and cellular user equipment in a multi-cell environment, we propose a resource allocation scheme and dynamic power control for D2D communication underlaying uplink cellular network. Specifically, by introducing the fractional frequency reuse (FFR) principle into the multi-cell architecture, we divide the cellular network into inner region and outer region. Combined with resource partition method, we then formulate the optimization problem so as to maximize the total throughput. However, due to the coupled relationship between resource allocation and power control scheme, the optimization problem is NP-hard and combinational. In order to minimize the interference caused by D2D spectrum reuse, we solve the overall throughput optimization problem by dividing the original problem into two sub-problems. We first propose a heuristic resource pairing algorithm based on overall interference minimization. Then with reference to uplink fractional power control (FPC), a dynamic power control method is proposed. By introducing the interference constraint, we use a lower bound of throughput as a cost function and solve the optimal power allocation problem based on dual Lagrangian decomposition method. Simulation results demonstrate that the proposed algorithm achieves efficient performance compared with existing methods.     

Spectrum efficiency sub-carrier and energy efficiency power allocation for downlink multi-user CoMP in multi-cell system

Coordinated multi-point transmission/reception （CoMP） was proposed currently as an effective technology to improve cell-edge throughput in next-generation wireless systems. Most of the existing work discussed clustering methods mostly to maximize the edge user throughput while neglecting the problem of energy efficiency, such as those algorithm clustering base stations （BSs） of better channel condition and BSs of worse channel condition together. In addition, BSs usually increase the transmit power to achieve higher throughput without any considering of interference caused to other users, that may result in energy waste. The authors focus on the throughput maximizing problem while fully considering energy saving problem in CoMP systems. A coefficient is defined to describe the fitness of clusters. Then a sub-carrier allocation algorithm with clustering method is put forward for CoMP downlink, which can save the transmit power of BS and increase the throughput. Furthermore a power allocation scheme is proposed based on non-cooperation game; in which the transmit power is decreased by BSs generally to reach the Nash equation （NE）. Simulation shows that the proposed sub-carrier allocation scheme and power allocation algorithm are better than the existing ones on users＇ throughput while consumes much less energy.