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

The subcarrier allocation problem in cognitive radio（CR）networks with multi-user orthogonal frequency-division multiplexing（OFDM）and distributed antenna is analyzed and modeled for the flat fading channel and the frequency selective channel,where the constraint on the secondary user（SU）to protect the primary user（PU）is that the total throughput of each PU must be above the given threshold instead of the ＂interference temperature＂.According to the features of different types of channels,the optimal subcarrier allocation schemes are proposed to pursue efficiency（or maximal throughput）,using the branch and bound algorithm and the 0-1 implicit enumeration algorithm.Furthermore,considering the tradeoff between efficiency and fairness,the optimal subcarrier allocation schemes with fairness are proposed in different fading channels,using the pegging algorithm.Extensive simulation results illustrate the significant performance improvement of the proposed subcarrier allocation schemes compared with the existing ones in different scenarios.

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.

WORST SUBCARRIER AVOIDING WATER-FILLING SUBCARRIER ALLOCATION SCHEME FOR OFDM-BASED CRN

Efficient and reliable subcarrier power joint allocation is served as a promising problem in cognitive OFDM-based Cognitive Radio Networks (CRN). This paper focuses on optimal subcarrier allocation for OFDM-based CRN. We mainly propose subcarrier allocation scheme denoted as Worst Subcarrier Avoiding Water-filling (WSAW), which is based on Rate Adaptive (RA) criterion and three constraints are considered in CRN. The algorithm divides the assignment procedure into two phases. The first phase is an initial subcarrier allocation based on the idea of avoiding selecting the worst subcarrier in order to maximize the transmission rate; while the second phase is an iterative adjustment process which is realized by swapping pairs of subcarriers between arbitrary users. The proposed scheme could assign subcarriers in accordance with channel coherence time. Hence, real time subcarrier allocation could be implemented. Simulation results show that, comparing with the similar existing algorithms, the proposed scheme could achieve larger capacity and a near-optimal BER performance.

Adaptive subcarrier allocation for MIMO-OFDMA wireless systems using Hungarian method

MIMO-OFDMA is a promising technique for future broadband wireless communication systems. In this paper, the problem of allocating subcarriers among different users to maximize the total capacity is addressed. The optimal solution can be obtained by Hungarian method is proved, using two utility matrices, i.e. the Frobenius-norm matrix and the determinant matrix. Simulation results show that the proposed algorithm can achieve higher capacity than the existing algorithms, and it is globally optimal and easy to be implemented.

Low complexity hybrid power distribution combined with subcarrier allocation algorithm for OFDMA

To improve the total throughput of the uplink orthogonal frequency division multiple access system,a low complexity hybrid power distribution（HPD） combined with subcarrier allocation scheme is proposed.For the fairness mechanism for the subcarrier,the inter-cell interference is first analyzed to calculate the capacity of the multi-cell.The user selects the subcarrier with the largest channel gain.Based on the above subcarrier allocation scheme,a new kind of HPD scheme is proposed,which adopts the waterfilling-power-distributed scheme and the equal-power-distributed scheme in the cell-boundary and the cellcenter,respectively.Simulation results show that compared with the waterfilling-power-distributed scheme in the whole cell,the proposed HPD scheme decreases the system complexity significantly,meanwhile its capacity is 2% higher than that of the equal-powerdistributed scheme over the same subcarrier allocation.

Adaptive Subcarrier Allocation for MIMO-OFDMA Wireless Systems Based on Beamforming

Beamforming is a kind of signal processing technique which can improve system performance in the multiple-input multiple-output(MIMO)systems.In this paper,the problem of allocating subcarriers in MIMO-OFDMA wireless systems was analyzed,and a scheme to allocate subcarriers among all users based on beamforming was proposed to maximize the signal-to-noise ratio(SNR)at the receiver.Statistical properties of the channel matrix were studied,and some beneficial results were got.Statistical channel state information(CSI)was also taken into account to simulate more practical systems.Simulation results show that the proposed allocating scheme is effective,and it is robust to the influence of delayed CSI.

BLOCK ADAPTIVE SUBCARRIER ALLOCATION FOR WIRELESS MULTIUSER OFDM SYSTEM

In this paper, a blockwise adaptive subcarrier allocation algorithm for multiuser Orthogonal Frequency Division Multiplexing (OFDM) system is introduced. Assuming the knowledge of channel information for all users, the algorithm minimizes the total transmit power while satisfying the total power and users' rate constraints. The result of simulation shows that the proposed algorithm reduces the average bit Signal-to-Noise Ratio (SNR) by approximately 4 dB compared with OFDM-Frequency Division Multiple Access (OFDM-FDMA), and supports more users in a multiuser Rayleigh fading channel. As assigning subcarriers in block, the computational complexity of the algorithm is much lower than that of the derivation of "water-filling" algorithm.

Genetic Algorithm Based QoS Aware Adaptive Subcarrier Allocation in Cognitive Radio Networks

In this paper, an adaptive subcarrier allocation scheme with reconfiguration of operating parameters for Cognitive Radio Networks (CRN) is presented. A QoS-conscious spectrum decision frame work is projected, where spectrum bands are determined by considering the application requirements as well as the dynamic nature of the spectrum bands. The novel subcarrier allocation algorithm is developed to fulfill different performance objective as a solution for subcarrier allocation and power allocation problem for Cognitive Radio (CR) users in CRNs. It employs operating frequency parameter modification using Proportional Resource Algorithm and Genetic Algorithm (GA). The multi objective optimization problem with equality and inequality constraint is considered. Moreover, a dynamic subcarrier allocations scheme is developed based on GA to decide on the spectrum bands adaptively dependent on the time-varying CR network capacity. The proposed algorithm targets to achieve maximum data rate for each subcarrier, maximize the overall network throughput and maximize the number of satisfied user under the constraints of bandwidth and guarantee Quality of Service (QoS) requirement from dynamic spectrum management (DSM) perspective. Moreover, it determines the best available channel.

A Low Complexity Algorithm for Subcarrier-and-Bit Allocation in OFDMA-Based LTE Systems

In this paper, we propose optimum and sub-optimum resource allocation and opportunistic scheduling solutions for orthogonal frequency division multiple access （OFDMA）-based multicellular systems. The applicability, complexity, and performance of the proposed algorithms are analyzed and numerically evaluated. In the initial setup, the fractional frequency reuse （FFR） technique for inter-cell interference cancellation is applied to classify the users into two groups, namely interior and exterior users. Adaptive modulation is then employed according to the channel state information （CSI） of each user to meet the symbol error rate （SER） requirement. There then, we develop subcarrier-and-bit allocation method, which maximizes the total system throughput subject to the constraints that each user has a minimum data rate requirement. The algorithm to achieve the optimum solution requires high computational complexity which hinders it from practicability. Toward this suboptimum method with the reduced to the order of O（NIO, the total number of subcarriers end, we complexity propose a extensively where N and K denote and users, respectively. Numerical results show that the proposed algorithm approaches the optimum solution, yet it enjoys the features of simplicity, dynamic cell configuration, adaptive subearrier-and-bit allocation, and spectral efficiency.

Power-Minimizing Resource Allocation in Multiuser Cooperative Relay Communications

In this paper, we investigate the power-minimizing resource allocation problem in multiuser cooperative relay communication systems. A joint optimization problem involving subcarrier assignment, relay selection and power allocation is formulated. Since the problem cannot be solved directly, we decompose it into three subproblems. According to the equivalent channel gains and the target rates of users, the subcarrier assignment and relay selection are conducted. Motivated by the water-filling algorithm, we propose a power allocation algorithm with cooperative features. Simulations results indicate that the proposed algorithm performs better in terms of the total transmit power consumption than the existing algorithms.

Energy efficient resource allocation for D2D multicast communications

The resource allocation for device-to-device(D2D)multicast communications is investigated.To achieve fair energy efficiency(EE)among different multicast groups,the max-min fairness criterion is used as the optimization criterion and the EE of D2D multicast groups are taken as the optimization objective function.The aim is to maximize the minimum EE for different D2D multicast groups under the constraints of the maximum transmit power and minimum transmit rate,which is modeled as a non-convex and mixed-integer fractional programming problem.Here,suboptimal resource allocation algorithms are proposed to solve this problem.First,channel assignment scheme is performed to assign channel to D2D multicast groups.Second,for a given channel assignment,iterative power allocation schemes with and without loss of cellular users’rate are completed,respectively.Simulation results corroborate the convergence performance of the proposed algorithms.In addition,compared with the traditional throughput maximization algorithm,the proposed algorithms can improve the energy efficiency of the system and the fairness achieved among different multicast groups.

Green Resource Allocation for Multiple OFDMA Based Networks: A Survey

Orthogonal frequency division multiple access （OFDMA） is a popular and widely accepted multiple access technique to provide high data rate services in a mobile environment in the area of wireless communications. OFDMA can provide better flexibility in allocating the radio spectra by utilizing subcarrier allocations, scheduling, and energy control to obtain multi-dimension diversity gains. Due to its resource allocation flexibility, OFDMA has been widely used as a green air interface technology for the emerging broadband wireless access networks. This paper extensively addresses the integration of green OFDMA to the future air interface technologies, for instance： two-tier cellular, multi radio access technologies （RATs）, FemtoCell, and relay networks. The main focus of the paper is to review and analyze the current OFDMA techniques to address the green resource allocation in multiuser diversity, where the critical constraints are the computational complexity, energy efficiency, and the sub-channel assignment. The future trend of OFDMA based networks will aim to maximize the energy efficiency of the exclusive channel assignment through a joint sub-channel and power allocation to accommodate high data traffic networks specially the relay based 5G cellular networks.

Multiuser subcarriers and bit allocation combining adaptive mapping for SC-FDMA system

In this article, a multiuser single carrier frequency division multiple access （SC-FDMA） system is considered, based on which an adaptive subcarrier and bit allocation algorithm is investigated. The algorithm has been used to achieve a subcarrier mapping mode in this system, which combines the advantages of single- and multi-carrier transmissions, such as, low peak to average power ratio, orthogonality of signals of different users, and low complexity. Simulation results show that it has a similar performance as that of the adaptive allocation algorithm in the orthogonal frequency division multiple （OFDM） system and the proposed mapping mode has a performance gain over the two existing mapping modes at the link level.

基于频分多址的多用户OFDM通信雷达一体化方案

通信雷达一体化(RadCom)被认为是下一代通信技术的重要研究方向,受到了学术界和工业界的广泛关注。研究了基于频分多址(FDMA)的多用户OFDM RadCom方案,其关键问题在于多用户子载波分配方式。不同的子载波分配方式会导致雷达距离处理出现不同的旁瓣水平,从而影响雷达的测距性能,在子载波采用连续分配和随机分配方式的情况下,各用户在雷达距离处理时会出现明显的旁瓣,雷达测距性能退化严重。为了找到适当的子载波分配方式,使得各用户的雷达距离处理的旁瓣水平尽可能低,以距离观测窗内的综合旁瓣水平作为代价函数,发现在用户数受限的情况下,子载波采用等间隔分配方式时,代价函数取得最小值,所有用户的旁瓣水平在距离观测窗内最低,各用户都能够有效地实现雷达探测功能。最后,在车联网(IoV)场景下,对不同的子载波分配方式进行仿真和对比,验证了子载波等间隔分配的有效性。

雷达通信一体化子载波和功率联合分配方法

雷达通信一体化系统是缓解无线电频谱拥塞和频谱资源短缺的高效解决方案。在雷达的最小信号噪声比和最小通信传输速率的约束条件下,通过构建混合整数非线性优化模型,提出了子载波和功率联合分配方法,实现系统总发射功率的最小化。首先将优化模型转化为线性模型并添加罚因子,然后选择用于雷达或通信目的的子载波。考虑到雷达性能和通信性能评价标准的差异,对用于雷达或通信目的子载波设置不同的发射功率约束,最终通过循环优化实现子载波和功率的联合分配。数值仿真结果表明,所提方法显著节约了功率资源。

基于可见光的通信定位一体化技术研究

可见光无线技术通过可见光传递信息,利用发光二极管(LED)光源在照明的同时实现通信和定位。可见光通信定位一体化(VLCP)技术是未来大规模物联网(IoT)应用的关键支撑技术之一。采用正交频分复用(OFDM)技术可将不同的频谱资源分别分配给可见光通信(VLC)和可见光定位(VLP)系统,同时实现通信和定位功能。资源分配是提升VLCP系统效率、拓展VLCP系统适用范围的关键所在。提出了一种基于误差矢量幅度(EVM)的新型资源分配方法,利用EVM分配VLCP系统中用于定位和通信的子载波,依据信道参数动态调整通信与定位性能,保证系统服务质量(QoS),提升系统信道利用率。实验结果表明,在1.5 m×1.5 m×1.5 m的室内环境下,提出的资源分配算法比固定资源分配算法至少可提高19.5%的信道利用率,在与采用信噪比(SNR)进行资源分配的算法性能相当的前提下,可大大节省系统资源,易于实际应用。

基于多臂赌博机的卫星通信系统子载波分配算法

为了提升卫星通信系统的频谱效率,在卫星系统采用正交频分多址(Orthogonal Frequency Division Multiple Access,OFDMA)传输技术的情况下,提出了一种基于多臂赌博机(Multi⁃Armed Bandit,MAB)的子载波分配算法。首先,建立基于OFDMA的卫星系统上行链路多用户传输模型。然后建立以用户总速率最大化为目标,以用户最大发射功率和用户服务质量为约束条件的资源分配问题。接着,利用MAB能在环境信息部分未知时在线学习摇臂选择策略的特性来求解该优化问题,并获得子载波分配方案。仿真结果表明,所提算法能实现系统子载波的自适应分配,同时用户总速率与贪婪算法在已知信道状态信息下获得的用户总速率几乎相同。

基于HPLC的物联网通信技术研究

针对宽带电力线载波通信资源分配问题,提出一种物理层资源分配算法,满足低复杂度的需求。首先,基于等功率分配方法,确定每个用户满足其最小速率要求所需的子载波集合,资源分配中的多用户问题可以拆分为单用户问题,并满足最优功率分配,然后将拉格朗日乘子法用于优化每个用户使用的子载波集的功率,以进一步提高系统吞吐量。仿真分析表明,所提算法具有更高的吞吐量,比最大吞吐量算法和Gong算法提高了13.52%和5.61%,能够满足用户的最低速率要求。

基于资源利用率的可重构无源光通信网络

为了提升网络带宽容量、降低网络时延,提出基于资源利用率的可重构无源光通信网络。通过可重构平台的网络管理构件、数据采集构件、P2P重定向构件共同配合,建立可重构无源光通信网络,依据可重构无源光通信网络层间信息互通特点,在网络物理层上添加MAC层,设计基于MAC-RPON层的资源分配模型,MAC层依据用户队列内调度事宜轻重程度,将所有队列数据包按照优先级别排序,物理层通过可重构无源光通信网络的准入、带宽分配和频谱分配三个步骤,将子载波合理分配给每个用户。实验分析表明:所研究网络可有效完成资源分配,且网络带宽容量大,更好地满足资源合理利用需求;网络平均队列长度短,资源分配时延低、效率快,有效提升网络资源利用率。

认知无线电网络子载波和功率分配

在干扰温度和总发送功率的限制条件下,提出了一种基于正交频分多址(OFDMA)接入方式的认知无线电网络上行链路子载波和功率分配算法,目标为最大化系统吞吐量.算法在初始分配方案的基础上不断调整,最终逼近最优分配方案.仿真结果表明,所提算法在大幅度降低计算复杂度的同时,达到了接近穷举方案的性能.