A New Power Allocation Algorithm in Cognitive Radio Networks

Most resource allocation algorithms are based on interference power constraint in cognitive radio networks. Instead of using conventional primary user interference constraint, we give a new criterion called allowable signal to interference plus noise ratio （SINR） loss constraint in cognitive transmission to protect primary users. Considering power allocation problem for cognitive users over flat fading channels, in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user, we propose a new power allocation algorithm. The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.     

OFDMA分布式无线接入网络中基于共享标准的资源分布研究

Distributed radio access network (DRAN) is a novel wireless access architecture and can solve the problem of the available spectrum scarcity in wireless communications. In this paper, we investigate resource allocation for the downlink of OFDMA DRAN. Unlike previous exclusive criterion based algorithms that allocate each subcarrier to only one user in the system, the proposed algorithms are based on shared criterion that allow each subcarrier to be allocated to multiple users through different antennas and to only one user through same antenna. First, an adaptive resource allocation algorithm based on shared criterion is proposed to maximize total system rate under each user’s minimal rate and each antenna’s maximal power constraints. Then we improve the above algorithm by considering the influence of the resource allocation scheme on single user. The simulation results show that the shared criterion based algorithm provide much higher total system rate than that of the exclusive criterion based algorithm at the expense of the outage performance and the fairness, while the improved algorithm based on shared criterion can achieve a good tradeoff performance.     

Cross-layer resource allocation for QoS guarantee with finite queue constraint in multirate OFDMA wireless networks

Efficient radio resource allocation is essential to provide quality of service （QoS） for wireless networks. In this article, a cross-layer resource allocation scheme is presented with the objective of maximizing system throughput, while providing guaranteed QoS for users. With the assumption of a finite queue for arrival packets, the proposed scheme dynamically a/locates radio resources based on user＇s channel characteristic and QoS metrics derived from a queuing model, which considers a packet arrival process modeled by discrete Markov modulated Poisson process （dMMPP）, and a multirate transmission scheme achieved through adaptive modulation. The cross-layer resource allocation scheme operates over two steps. Specifically, the amount of bandwidth allocated to each user is first derived from a queuing analytical model, and then the algorithm finds the best subcarrier assignment for users. Simulation results show that the proposed scheme maximizes the system throughput while guaranteeing QoS for users.     

Adaptive Power and Bit Allocation in Multicarrier Systems

We present two adaptive power and bit allocation algorithms for multicarrier systems in a frequency selective fading environment. One algorithm allocstes bit based on maximizing the channel capacity, another allocates bit based on minimizing the bit-error-rate （BER）. Two algorithms allocate power based on minimizing the BER. Results show that the proposed algorithms are more effective than Fischer＇s algorithm at low average signal-to-noise ration （SNR）. This indicates that our algorithms can achieve high spectral efficiency and high communication reliability during bad channel state. Results also denote the bit and power allocation of each algorithm and effects of the number of subcarriers on the BER performance.     

Subcarrier and power allocation algorithm based on inter-cell interference mitigation for OFDMA system

This article proposes a dynamic subcarrier and power allocation algorithm for multicell orthogonal frequency division multiple access (OFDMA) downlink system, based on inter-cell interference (ICI) mitigation. Different from other ICI mitigation schemes, which pay little attention to power allocation in the system, the proposed algorithm assigns channels to each user, based on proportional-fair (PF) scheduling and ICI coordination, whereas allocating power is based on link gain distribution and the loading bit based on adaptive modulation and coding (AMC) in base transceiver station (BTS). Simulation results show that the algorithm yields better performance for data services under fast fading.     

Utility-Based Joint Scheduling Approach Supporting Multiple Services for Co MP-SUMIMO in LTE-A System

In this paper, we study utility-based resource allocation for users supporting multiple services in a LTE-A system with coordinated multi-point transmission for single-user multi-input multi-output(Co MP-SU-MIMO). We designed Joint Transmission Power Control(JTPC) for the selected clusters for minimizing power consumption in LTE-A systems. The objective of JTPC is to calculate the optimal transmission power for each scheduled user and subcarrier. Moreover, based on the convex optimization theory, we propose the dynamic sector selection method in which the average sector throughput and cell-edge users(UEs) rates are performed to achieve the optimal solution. Simulation results show that the system performance achieved by using the proposed suboptimal algorithm is close to that achieved by the dual decomposition method.     

Dynamic subcarrier and power allocation based on cooperative game theory in symmetric cooperative OFDMA networks

In order to improve the efficiency and fairness of radio resource utilization,a scheme of dynamic cooperative subcarrier and power allocation based on Nash bargaining solution(NBS-DCSPA) is proposed in the uplink of a three-node symmetric cooperative orthogonal frequency division multiple access(OFDMA) system.In the proposed NBS-DCSPA scheme,resource allocation problem is formulated as a two-person subcarrier and power allocation bargaining game(SPABG) to maximize the system utility,under the constraints of each user’s maximal power and minimal rate,while considering the fairness between the two users.Firstly,the equivalent direct channel gain of the relay link is introduced to decide the transmission mode of each subcarrier.Then,all subcarriers can be dynamically allocated to the two users in terms of their selected transmission mode.After that,the adaptive power allocation scheme combined with dynamic subcarrier allocation is optimized according to NBS.Finally,computer simulation is conducted to show the efficiency and fairness performance of the proposed NBS-DCSPA scheme.     

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.     

Power allocation in cooperative MIMO systems under individual power constraints

Power allocation(PA)plays an important role in capacity improvement for cooperative multiple-input multiple-output(Co-MIMO)systems.Many contributions consider a total power constraint(TPC)on the sum of transmit power from all nodes in addressing PA problem.However,in practical implementations,each transmit node is equipped with its own power amplifier and is limited by individual power constraint(IPC).Hence these PA methods under TPC are not realizable in practical systems.Meanwhile,the PA problem under IPC is essential,but it has not been studied.This paper extends the traditional non-cooperative water-filling PA algorithm to IPC-based Co-MIMO systems.Moreover,the PA matrix is derived based on the compound channel matrix from all the cooperative nodes to the user.Therefore,the cooperative gain of the IPC-based Co-MIMO systems is fully exploited,and further the maximal instantaneous capacity is achieved.Numerical simulations validate that,under the same IPC conditions,the proposed PA scheme considerably outperforms the non-cooperative water-filling PA and uniform PA design in terms of ergodic capacity.     

Downlink CoMP Resource Allocation Based on Limited Backhaul Capacity

Coordinated Multi-Point(CoMP) transmission is put forward in the Long Term Evolution-Advanced(LTE-A) system to improve both average and cell-edge throughput. In this paper, downlink CoMP(DL-CoMP) resource allocation scheme based on limited backhaul capacity is designed to take a tradeoff between system throughput and fairness. Resource allocation of proportional fairness based on querying table is proposed. It updates RB allocation matrix when center cell has completed resource allocation and delivers the matrix to adjacent cells for their own RB allocation. Furthermore, Water-Filling algorithm based on adaptive water level(AWF) is used for power allocation to boost system fairness. In this paper, performance of downlink CoMP based on limited backhaul capacity and single-point transmission is contrasted, and results indicate that CoMP dramatically enhances system throughput and spectral efficiency. Moreover, AWF power allocation scheme obtains higher system fairness than conventional Water-Filling(WF) algorithm, although it gets slightly lower system throughput. Finally, this paper discussed that the system performance is partially affected by the percentage of CoMP resource.     

一种低复杂度MIMO-OFDMA系统的自适应子载波分配算法

本篇论文提出一种多用户多输入多输出正交频分复用系统(MIMO-OFDMA)下行链路具有信道变化实时性的动态子载波分配算法.文中采用奇异置分解,将每个子载波的MIMO衰落信道分解为独立的并行子信道,利用子信道通对各子载波容量的求解推导出本文算法.此次优的算法在满足各个用户数据速率和BER要求的同时,能减小发射功率.仿真结果也证明了这一点.     

Improving Water-Filling Algorithm to Power Control Cognitive Radio System Based Upon Traffic Parameters and QoS

Cognitive radio scenario is based upon the ability to determine the radio transmission parameters from its surrounding environment. Power allocation in cognitive radio systems improves secondary network capacity subject to primary receiver interference level threshold. In this paper, statistical property of the injected interference power in primary user channel is used to establish the container bottom for each subcarrier employing water filling algorithm. In other words, the container bottom level of each subcarrier depends on the injected interference in primary user (PU) (most probably from the overloaded neighbor subcarriers). Traffic statistical parameters are also employed to formulate power allocation problem. Within this context, quality of service constraint is considered also to improve performance of power allocation algorithm. Simulation Results show that the injected interference in PU is decreased while the secondary user capacity improves. Indeed, the proposed algorithm is more compatible than a waterfilling algorithm with cognitive radio system constraints.     

A Low Complexity Resource Allocation Method for OFDMA System Based on Channel Gain

In orthogonal frequency division with multiple access (OFDMA) systems dynamic radio resource allocation improves overall performance by exploiting the multiuser diversity gains. A key issue in OFDMA is the allocation of the OFDM subcarriers and power among users sharing the channel. This paper proposes a new rate adaptive resource allocation scheme in the OFDMA downlink transmission system. Our proposed algorithm is based on the users’ sensitivity to the subcarrier allocation which means how frequency selective is the channel from the user’s perspective. As a result of frequency selectivity of the channel, different subchannels of the same user experience different levels of fade. However, how different they undergo fading could be measured by difference between maximum and minimum channel gain of that user. Our proposed method is based on difference between maximum channel gain and minimum channel gain for each user and uniform distribution of power among subcarriers. Simulation results show that the proposed algorithm achieves higher capacity over fixed TDMA method, and reported suboptimal methods with acceptable rate proportionality.     

基于Schmidt正交化的多天线选择复用

该文从提高信道传输有效性的角度,提出了一种新的多天线选择发送策略--贪婪搜索(GS)法,使用这种方法挑选出使容量最大化的发送天线组合作为传输信号的天线。此法在结合注水(waterfilling)法进行天线功率分配的情况下,与理想的全天线注水法相比,可以减小发射机的复杂度,在独立信道下传输容量略有损失,在相关信道下可以提高传输容量,并且所付出的代价是仅需要对信道矩阵进行Schmidt正交化变换。这种方法一般用于信道矩阵列不满秩,即发送端天线数大于接收端天线数,发送端已知信道矩阵的情况(与注水法结合)或者接收端已知信道矩阵的情况(等功率分配)。     

多用户OFDM系统中一种新颖的自适应功率分配方案

针对多用户正交频分复用(OFDM)系统自适应资源分配的问题,提出了一种新的自适应子载波分配方案。子载波分配中首先通过松弛用户速率比例约束条件确定每个用户的子载波数量,然后对总功率在所有子载波间均等分配的前提下,按照最小比例速率用户优先选择子载波的方式实现子载波的分配;在功率分配中提出了一种基于人工蜂群算法和模拟退火算法(ABC-SA)相结合的新功率分配方案,并且通过ABC-SA算法的全局搜索实现了在所有用户之间的功率寻优,同时利用等功率的分配方式在每个用户下进行子载波间的功率分配,最终实现系统容量的最大化。仿真结果表明,与其他方案相比,所提方案在兼顾用户公平性的同时还能有效地提高系统的吞吐量,进而证明了所提方案的有效性。     

Capacity Optimizing Power Allocation in Interference Channels

The interference channel is an essential model in both wireline and wireless communication systems. This article addresses transmit power allocation in interference channels with total transmit power constraint. The optimum power allocation maximizing the sum rate in two user interference channels can be derived analytically. However, the non-convexity of the optimization problem makes it prohibitively complex to obtain the optimum solution either analytically or numerically in general K user scenarios. After reviewing several conventional suboptimum power allocation schemes including equal power allocation, greedy power allocation and waterfilling power allocation, an iterative waterfilling algorithm is proposed and discussed. The performance of various power allocation schemes is evaluated through simulations, which suggests that the proposed iterative waterfilling outperforms other suboptimum power allocation schemes in certain scenarios.     

Block diagonalization coordinated transmission with zero-forcing in MIMO broadcast

This work has investigated coordinated multiple-input multiple-output (MIMO) transmission schemes in an interference-limited cellular downlink. It has proposed a novel block diagonalization (BD) coordinated transmission scheme, which combines with zero-forcing (ZF) criterion. In the scheme, the BD technique has advantages in suppressing multi-user interference while the ZF technique enables to mitigate interference among spatial data streams for a user. Based on the proposed coordinated scheme, an efficient power allocation is also put forward. The analyses show that the ergodic capacity of the proposed coordinated scheme is that of the MIMO channel with the maximum transmit power at each transmitter. Computer simulations demonstrate the effectiveness of the proposed coordinated scheme and its corresponding power allocation.     

Resource allocation for sum-rate maximization in NOMA-based generalized spatial modulation

The Multiple-Input Multiple-Output (MIMO) Non-Orthogonal Multiple Access (NOMA) based on Spatial Modulation (SM-MIMO-NOMA) system has been proposed to achieve better spectral efficiency with reduced radio frequency chains comparing to the traditional MIMO-NOMA system. To improve the performance of SM-MIMO-NOMA systems, we extend them to generalized spatial modulation scenarios while maintaining moderate complexity and fairness. In this paper, system spectral efficiency and transmission quality improvements are proposed by investigating a sum-rate maximization resource allocation problem that is subject to the total transmitted power, user grouping, and resource block constraints. To solve this non-convex and difficult problem, a graph-based user grouping strategy is proposed initially to maximize the mutual gains of intragroup users. An auxiliary-variable approach is then adopted to transform the power allocation subproblem into a convex one. Simulation results demonstrate that the proposed algorithm has better performance in terms of bit error rate and sum rates.     

多用户MIMO-OFDM系统中的资源分配

该文针对多用户MIMO-OFDM系统,基于最大化信号与干扰加噪声比(Signal-to Jamming and Noise Ratio,SJNR)预编码,提出了实用的自适应资源分配方法。根据各用户SJNR值,提出采用递增(Incremental Algorithm,IA)和递减(Decremental Algorithm,DA)两种方法为各子载波选择用户集合,使各子载波被多个用户最优复用,实现多用户分集,以达到最大化系统吞吐量的目的。此外,基于DA思想,给出了考虑不同用户QoS要求下分配子载波的方法(QoS Decremental Algorithm,QDA)。分析和仿真结果表明,IA和DA在大大降低算法复杂度的同时使性能很好地接近最优算法,QDA能在满足不同用户QoS要求的同时最大化系统吞吐量。     

Unsupervised Optimization for Universal Spatial Image Steganalysis

This paper presents adaptive per-spatial stream power allocation algorithms for Single User Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (SU MIMO-OFDM) systems. Three efficient and low-complexity Greedy Power Allocation (GPA) algorithms are proposed to maximize the throughput and spectral efficiency of the SU MIMO-OFDM systems. Firstly, the low-complexity pre-coded GPA algorithms are developed for the MIMO systems. The spatial sub-channels are created by applying the so-called Singular Value Decomposition (SVD) technique on the MIMO channel matrix, and then the Pre-GPA algorithms are applied to exploit the multi-path and spatial diversities. Secondly, the spatial and frequency diversities are exploited by adaptively allocating the system sub-carriers to the spatial sub-channels followed by Per-Spatial GPA (PSGPA). Finally, spatial multiplexing-based GPA algorithms are proposed to optimize the spectral efficiency of the SU MIMO-OFDM system. An optimal two-dimensional Spatial-Frequency GPA (SFGPA) algorithm is proposed to efficiently improve the average system spectral efficiency. The high computational complexity of the optimal SFGPA solution is simplified by proposing a low-complexity Per-Spatial GPA with Excess Power Moving down (PSGPA-EPMd) algorithm, which moves the per-spatial excess power downwards to enhance the spectral efficiency of the spatial multiplexing-based SU MIMO-OFDM systems. The proposed algorithms achieve better spectral efficiency and maximize the throughput in comparison with conventional algorithms.