Low Complexity Precoded Greedy Power Allocation Algorithms for OFDM Communication Systems

In this paper, an enhanced greedy bit and power allocation algorithms for orthogonal frequency division multiplexing (OFDM) communication systems are introduced. These algorithms combine low complexity greedy power allocation algorithms with a simplified maximum ratio combining (MRC) precoding technique at the transmitter for maximizing the average data throughput of OFDM communication systems. Results of computer simulations show that precoding is an effective technique for improving the throughput performance of the proposed bit and power allocation algorithms.

Resource allocation for multiuser STBC-BF MIMO-OFDM downlink with imperfect channel information

To improve the performance of a multiuser MIMO-OFDM system with imperfect channel status information, a downlink adaptive resource allocation algorithm which combines space-time block coding and beam forming （STBC-BF） is proposed. The algorithm allocates the subcarriers with a shared manner. A zero forcing processing with joint Rx-Tx is used to suppress the co-channel interference （CCI） and to construct uncorrelated channels for STBC. An adaptive power allocation for the STBC equivalent channels can increase signal to interference and noise ratio at the receiver. Simulation results show that under the condition of an imperfect CSI, the proposed algorithm improves the system performance and reduces the number of BS transmit antennas required.

分布式残余频偏信道中的Alamouti STBC-OFDM功率分配

在具有不同残余频偏的分布发射天线多径瑞利衰落信道中,该文使用Cholesky判决反馈检测的Alamouti STBC-OFDM链路,提出了一种抑制残余频偏影响的发射功率分配方法:以最小化残余频偏下链路的平均误比特率下界为准则,为发射天线分配功率。首先推导了残余频偏下链路的平均误比特率下界,然后给出了发射天线间最优功率分配因子的闭合解。仿真结果表明,与传统的假设频率理想同步的功率分配方法相比,在残余频偏对性能影响占主导作用的场景中,该文方法提升了链路性能,提升程度随着两根发射天线到接收机间平均信道功率增益之比的增加而增大。

Power allocation for MIMO-OFDM systems with multi-user decoupling and scheduling

A power allocation scheme for multi-user multiple-input multiple-output orthogonal frequency division multiplexing （MI- MO-OFDM） systems with channel state information （CSI） on transmitter and receiver is pressed. Multi-user lower allocation can be decoupled into single user lower allocation throughout null space mapping of multi-user channel and lower allocation can be performed throughout spatial-spectral water-filling for per user.To deal with more users in system and fading correlation,scheduling is oerformed to maintain the gain of power allocation.The proposed scheme can substantially improve system＇s spectral efficiency with low complexity.Simulation results validate the accuracy of theoretic analyses.

POWER ALLOCATION AND ADAPTIVE MODULATION STRATEGY FOR MIMO-OFDM SYSTEMS WITH IMPERFECT CSI

The presented scheme named M-CAP (Maximum CAPacity) uses the CSI (Channel State Information) and its statistics to deduce an equivalent channel according to which the transmit power is allocated to the subchannels. And then modulation scheme is determined adaptively according to the power allocated to each subchannel. The advantage of the M-CAP scheme is that it combines power allocation and adaptive modulation while maintaining a large capacity. We demonstrate by computer simulations that the proposed M-CAP scheme can significantly improve system performance compared with the traditional schemes.

基于天线选择的自适应OFDM-STBC发射分集

基于空时分组码的正交频分复用技术(OFDM-STBC)是多天线多载波技术,将自适应功率分配技术用于OFDM-STBC,如何在载波和天线间分配能量是个关键问题。将待发射的信息分配到最有利的天线上传输接着利用载波间功率分配的算法进行载波间的功率分配,该算法的目标是使误码率最小。通过量化信道衰落简化了功率分配算法实现;通过量化功率分配因子的方式提高了无线链路的利用率。仿真结果显示:在误码率取0.1%时,对于有4个子载波的系统,较传统的算法,此算法能带来5 dB的增益;随着系统载波数目的增加,性能进一步得到提高。

Joint Subcarrier and Power Allocation for Multi-UAV Systems

This paper investigates subcarrier and power allocation in a multi-UAV OFDM system.The study considers a practical scenario,where certain subcarriers are unavailable for dynamic subcarrier allocation,on account of pre-allocation for burst transmissions.We first propose a novel iterative algorithm to jointly optimize subcarrier and power allocation,so as to maximize the sum rate of the uplink transmission in the multiUAV OFDM system.The key idea behind our solution is converting the nontrivial allocation problem into a weighted mean square error(MSE) problem.By this means,the allocation problem can be solved by the alternating optimization method.Besides,aiming at a lower-complexity solution,we propose a heuristic allocation scheme,where subcarrier allocation and transmit power allocation are separately optimized.In the heuristic scheme,closedform solution can be obtained for power allocation.Simulation results demonstrate that in the presence of stretched subcarrier resource,the proposed iterative joint optimization algorithm can significantly outperform the heuristic scheme,offering a higher sum rate.

相关信道下基于多用户STBC-OFDM系统的子载波分配

针对多用户空时分组码—正交频分复用(STBC-OFDM)下行链路系统,以总发射功率最小化为优化目标,给出一种在空间相关瑞利衰落信道下基于部分信道状态信息(CSI)的自适应子载波分配算法。该算法利用克罗内克(Kronecker)模型表示每个子载波对应的空间相关多输入多输出(MIMO)瑞利衰落信道,并通过动态发射端的信道状态信息(CSIT)模型来描述CSI的反馈过程,从而应用STBC的基本原理推导出相应的子载波分配原则。实验结果表明,该算法不仅能有效地反映天线相关矩阵中相关系数以及延时反馈参数对系统性能的影响,而且与未利用CSIT模型的子载波分配相比具有较好的性能。

基于STBC MIMO-OFDM系统特性的并行选择映射算法

正交频分复用(OFDM)技术是第四代移动通信系统的核心技术之一,但是高峰均功率比(PAPR)问题的存在一直是该技术实用化的主要障碍.针对该问题,证明了基于空时分组码的MIMO-OFDM系统中,共轭信号具有相同的峰均功率比特性,提出了基于相同峰均比特性的并行选择映射算法.所提算法不仅保持了已有并行选择映射算法的峰均比降低性能,同时有效地减少了算法复杂度,降低了边带信息的传输量,提高了系统的频带利用率.仿真实验结果证明了所提算法的有效性.

多用户OSTBC-OFDM系统的自适应子载波分配研究

研究了基于正交空时分组码的多用户OFDM系统的自适应子载波分配算法.首先从性能角度出发,在保证用户误码率约束的前提下,以总的发射功率最小为目标,推导了具有普遍意义的OSTBC-OFDM的子载波分配通式.考虑到实际应用系统中效率与公平的折中,对各个用户定义相应的速率约束,以增加功率最小为原则,给出了改进的兼顾公平的子载波分配算法的具体步骤.数值仿真结果证明,自适应子载波分配能改善OSTBC-OFDM系统的误码率性能,且兼顾公平的算法需要一定的性能损失为代价.

Efficient Power Loading in MIMO-OFDM Based Cognitive Radio Networks

Due to their spectrum shaping capability and high adaptability, the multi-carrier systems are considered as prime candidates for use in the Cognitive Radio (CR) networks. In these structures, the deactivation of the primary users’ (PUs) bands makes the secondary users (SUs) use a limited number of sub-carriers, so the total capacity of CR networks is reduced. However, multiple transmit antennas can be applied to OFDM- based CR to compensate for such a low capacity. The present study investigates the problem of power allo-cation in MIMO-OFDM based CR Networks. The objective is maximizing the total capacity of CR systems in the downlink path under both interference on the PUs’ bands and maximum power of the CR transmitter constraints. It is shown that the optimal solution has high computational complexity, and therefore, an effi-cient sub-optimal algorithm is suggested for this application. As simulation results show, the suggested algo-rithm in the present paper is more enhanced and efficient than the previous algorithms.

非理想CSI下基于OSTBC的MIMO-OFDM系统中自适应资源分配算法研究

对于MIMO-OFDM系统,自适应资源分配可以有效利用时间、效率、空间等资源,进一步提高系统性能,其设计依赖于信道状态信息(CSI)的质量。但在实际系统中,信道估计本身可能存在误差,信道信息需要进行量化才能进行反馈,反馈信道可能经历衰落,存在时延,这些都会导致CSI的非理想,从而降低自适应资源分配所带来的性能提高,甚至消失。为了解决这个问题,文章给出了一种可使MIMO-OFDM系统在自适应传输模式(AT)及非自适应传输模式(Non-AT)这两种模式间进行切换的算法,即STM算法。仿真结果表明,根据给定CSI非理想反馈参数的不同,最优传输模式视情况而定。

AN EFFECTIVE SUBOPTIMAL POWER LOADING SCHEME IN OFDM-BASED COGNITIVE RADIO SYSTEMS

Orthogonal frequency division multiplexing(OFDM) is an attractive modulation candidate for Cognitive Radio(CR) networks.Effective and reliable subcarrier power allocation in OFDM-based Cognitive Radio(CR) networks is a challenging problem.This paper focuses on the power allocation for OFDM-based Cognitive Radio(CR) networks.Our objective is to maximize the total transmission rates of Secondary Users(SU) by adjusting the power of subcarrier while the interference introduced to the Primary User(PU) is within a certain range and the total power of subcarrier is not beyond the total power constraint.We investigate the optimal power allocation algorithm for OFDM-based Cog-nitive Radio(CR) based on convex optimization theory.Then,because of high complexity of the op-timal power allocation algorithm,we propose an effective suboptimal power loading scheme.Theory analysis and simulation results show that the performance of the suboptimal power allocation algorithm is close to the performance of the optimal power allocation algorithm,while the complexity of the suboptimal power allocation algorithm is much lower.

Joint Subcarrier and Power Allocation for DF-Based Multiuser Two-Way Relay Networks

Two-way decode-and-forward(DF) relay technique is an efficient method to improve system performance in 5G networks.However,traditional orthogonal frequency division multiplexing(OFDM) based two-way relay systems only consider a per-subcarrier relay strategy,which treats each subcarrier as a separate channel,which results in significant sum rate loss,especially in fading environments.In this paper,a joint coding scheme over multiple subcarriers is involved for multipair users in two-way relay systems to obtain multiuser diversity.A generalized subcarrier pairing strategy is proposed to permit each user-pair to occupy different subcarriers during the two transmission phases,i.e.,the multiple access and broadcast phases.Moreover,a low complexity joint resource allocation scheme is proposed to improve the spectrum efficiency with an additional multi-user diversity gain.Some numerical simulations are finally provided to verify the efficacy of our proposal.

Optimal power allocation for multi-user OFDM and distributed antenna cognitive radio with RoF

In cognitive radio （CR）,power allocation plays an important role in protecting primary user from disturbance of secondary user. Some existing studies about power allocation in CR utilize ＇interference temperature＇ to achieve this protection,which might not be suitable for the OFDM-based CR. Thus in this paper,power allocation problem in multi-user orthogonal frequency division multiplexing （OFDM） and distributed antenna cognitive radio with radio over fiber （RoF） is firstly modeled as an optimization problem,where the limitation on secondary user is not ＇interference temperature＇,but that total throughput of primary user in all the resource units （RUs） must be beyond the given threshold. Moreover,based on the theorem about maximizing the total throughput of secondary user,equal power allocation algorithm is introduced. Furthermore,as the optimization problem for power allocation is not convex,it is transformed to be a convex one with geometric programming,where the solution can be obtained using duality and Karush-Kuhn-Tucker （KKT） conditions to form the optimal power allocation algorithm. Finally,extensive simulation results illustrate the significant performance improvement of the optimal algorithm compared to the existing algorithm and equal power allocation algorithm.

Energy efficiency based multi-relay selection and power allocation in OFDM cooperation networks

Getting along with the improvement of green communications, the energy efficiency （EE） of wireless network becomes more and more important. However, in nmlti-relay-assisted systems, the related work obviously depends on the end-to-end performance, whereas EE of relays has not attracted enough attention. The authors propose an orthogonal frequency division multiplexing （OFDM） multi-relay system based on amplify and forward （AF） mode. Taking incorporating EE and remaining energy as factor, decision criteria of attending cooperation is designed. The EE based asynchronous power iteration method is presented, and the existence and convergence of nash equilibrium （NE） is proven. Furthermore, a joint algorithm in subcarrier pairing, relay selection and power allocation is given. Genetic algorithm （GA） and iteration method are integrated to improve the convergence speed additionally. Simulation demonstrates the obvious improvement of EE, decrease of power consumption and increase of lifetime in relays of this algorithm with the constraint of minimum data transmission rate.

Joint power allocation and subcarrier pairing in OFDM-based cooperative relaying system

This paper proposes rate-maximized （MR） joint subcarrier pairing （SP） and power allocation （PA） （MR-SP＆PA）, a novel scheme for maximizing the weighted sum rate of the orthogonal-frequency-division multiplexing （OFDM） relaying system with a decode-and-forward （DF） relay. MR-SP＆PA is based on the joint optimization of both SP and power allocation with total power constraint, and formulated as a mixed integer programming problem in the paper. The programming problem is then transformed to a convex optimization problem by using continuous relaxation, and solved in the Lagrangian dual domain. Simulation results show that MR-SP＆PA can maximize the weighted sum rate under total power constraint and outperform equal power allocation （EPA） and proportion power allocation （PCG）.

Optimal power allocation for two-way relaying over OFDM using physical-layer network coding

In this paper, a network scenario of two-way relaying over orthogonal frequency division multiplexing （OFDM） is considered, in which two nodes intend to exchange the information via a relay using physical-layer network coding （PLNC）. Assuming that the full channel knowledge is available, an optimization problem, which maximizes the achievable sum rate under a sum-power constraint, is investigated. It is shown that the optimization problem is non-convex, which is difficult to find the global optimum solution in terms of the computational complexity. In consequence, a low-complexity optimal power allocation scheme is proposed for practice implementation. A link capacity diagram is first employed for power allocation on each subcarrier. Subsequently, an equivalent relaxed optimization problem and Karush-Kuhn-Tucker （KKT） conditions are developed for power allocation among each subcarrier. Simulation results demonstrate that the substantial capacity gains are achieved by implementing the proposed schemes efficiently with a low-complexity computational effort.

分布式残余频偏信道中STBC-OFDM的发射功率优化

在分布式残余频偏信道中,考虑多径瑞利衰落,针对采用判决反馈检测的两发射天线STBC-OFDM链路,提出了一种发射功率优化方法:根据平均信道功率增益、残余频偏方差以及噪声方差的大小,以最小化平均误比特率下界为目标,设置两分布发射天线的发射功率.仿真结果表明:相比于传统的各天线满功率发射方法,所提方法能够在节省发射功率的同时提高链路的误比特率性能.

干扰背景下OFDM系统自适应功率分配优化

OFDM自适应分配结合了自适应调制技术和自适应分配算法,自适应分配算法根据获取的信道状态信息为每个子载波分配比特数和功率,自适应调制根据自适应算法提供的比特数和功率参数,对子信道配置选择相应的调制方式,以实现子载波的比特和功率的分配,从而提升系统的性能。文章采用常见的几种自适应比特功率算法解决OFDM资源分配问题,分析和比较了这几种算法。数值结果表明Fischer算法比Hughes-Hartogs算法更容易影响系统信道容量,并且该算法计算复杂度相对低,易于实现。在相同的SNR下,采用Fischer算法解决比特功率分配问题,信道容量受干扰环境影响明显。