Maximized Channel Capacity Based Power Allocation Technique for Multi Relay Hybrid Decode-Amplify-Forward Cooperative Network

In this paper, a novel maximized channel capacity based power allocation using differential evolution (DE) algorithm for multi relay Hybrid Decode-Amplify-Forward cooperative network in a Rayleigh fading environment is proposed. The closed form expression for average channel capacity with the tight approximation is derived. The proposed parametric optimization problem is defined on basis of the decoding capability of the relay. Further, the relay powers are optimized using the optimized power allocation factor. The performance of the proposed technique is validated for different channel variances and for different relay locations. From the simulation analysis, it is observed that the proposed DE based power allocation scheme performs better than the existing equal power allocation scheme.     

Joint backhaul bandwidth and power allocation in heterogeneous cellular networks: A two‐level approach

We investigate the problem of joint downlink wireless backhaul bandwidth (WBB) and power allocation in heterogeneous cellular networks (HCNs). A WBB partitioning scheme is considered, which allocates the whole bandwidth between the macrocell and small cells for data transmission and backhauling. We formulate an optimization problem to maximize the weighted sum logarithmic utility function by jointly optimizing WBB portion and fronthaul power allocation of each base station with consideration of the backhaul capacity limitation on each small cell. In order to solve this joint optimization problem, we propose a hierarchical two‐level approach and decompose the original problem into two independent subproblems: the WBB allocation at the macrocell base station (MBS) and the power allocation at both the MBS and small cell base stations (SBSs). Accordingly, the optimal WBB portion and power allocation solutions are obtained, respectively. Furthermore, we develop a distributed algorithm to implement the joint WBB and power allocation. Numerical results verify the effectiveness of the proposed approach and analyze the impact of the weighted coefficient and backhaul capacity limitation on the network performance. In addition, significant performance gains can be achieved by the proposed approach over the benchmark.     

Optimum Power Allocation for Single-User MIMO and Multi-User MIMO-MAC with Partial CSI

We consider both the single-user and the multi-user power allocation problems in MIMO systems, where the receiver side has the perfect channel state information (CSI), and the transmitter side has partial CSI, which is in the form of covariance feedback. In a single-user MIMO system, we consider an iterative algorithm that solves for the eigenvalues of the optimum transmit covariance matrix that maximizes the rate. The algorithm is based on enforcing the Karush-Kuhn-Tucker (KKT) optimality conditions of the optimization problem at each iteration. We prove that this algorithm converges to the unique global optimum power allocation when initiated at an arbitrary point. We, then, consider the multi-user generalization of the problem, which is to find the eigenvalues of the optimum transmit covariance matrices of all users that maximize the sum rate of the MIMO multiple access channel (MIMO-MAC). For this problem, we propose an algorithm that finds the unique optimum power allocation policies of all users. At a given iteration, the multi-user algorithm updates the power allocation of one user, given the power allocations of the rest of the users, and iterates over all users in a round-robin fashion. Finally, we make several suggestions that significantly improve the convergence rate of the proposed algorithms.     

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.     

协作系统中基于比例公平的资源分配方法

针对多用户协作中继系统中的资源分配问题,提出了一种在满足用户速率比例公平约束条件下的新算法。该算法先将由2个时隙组成的中继用户传输链路转换为一个等效信道链路,将涉及子载波分配、中继选择和功率分配的组合优化问题转化为分步的次优化问题。该算法在等功率分配情况下,根据各用户速率比例公平系数进行初步子载波数目分配;以瞬时信道增益最佳原则,进行剩余子载波数目分配及具体子载波分配,同时完成中继选择;在速率比例公平约束条件下推导出次优化功率分配的闭式表达式,从而完成各子载波上的功率分配。仿真结果表明,该算法在有效提高系统容量的同时,保证了各用户速率之间的比例公平性。     

Low‐complexity energy efficient power allocation scheme for DAS with maximum power constraint

In this paper, a low‐complexity optimal power allocation (PA) scheme is developed to maximize energy efficiency (EE) in a distributed antenna system (DAS) under maximum power constraint and target bit error rate (BER) requirement. Composite Rayleigh fading, multiple receive antennas, and dynamic circuit power consumption are all considered in the system. Unlike conventional schemes, the presented scheme provides a closed‐form expression of PA. Firstly, the optimization problem is formulated according to the definition of EE. Using the Karush‐Kuhn‐Tucker conditions, a general form of the optimal PA, in which the number of active antennas and corresponding power allocation are required only, is then proposed. With this general form, an effective algorithm is presented to yield the closed‐form PA. The proposed scheme can be applied to the system with static circuit power consumption and/or without target BER constraint to obtain optimal PA. Simulation results corroborate the effectiveness of the developed scheme, and the scheme can achieve the same EE performance as the existing optimal schemes with lower complexity. Moreover, the distributed antenna system with multiple receive antennas has higher EE than that with single receive antenna.     

Optimal resource allocation in multiservice CDMA networks

This paper addresses the problem of dynamic resource allocation in a multiservice direct-sequence code-division multiple-access (DS-CDMA) wireless network supporting real-time (RT) and nonreal-time (NRT) communication services. For RT users, a simple transmission power allocation strategy is assumed that maximizes the amount of capacity available to NRT users without violating quality of service requirements of RT users. For NRT users, a joint transmission power and spreading gain (transmission rate) allocation strategy, obtained via the solution of a constrained optimization problem, is provided. The solution maximizes the aggregate NRT throughput, subject to peak transmission power constraints and the capacity constraint imposed by RT users. The optimization problem is solved in a closed form, and the resulting resource allocation strategy is simple to implement as a hybrid CDMA/time-division multiple-access strategy. Numerical results are presented showing that the optimal resource allocation strategy can offer substantial performance gains over other conventional resource allocation strategies for DS-CDMA networks.     

Power allocation scheme based on sum capacity maximization for signal‐to‐leakage‐and‐noise ratio precoded multiuser multiple‐input single‐output downlink

This paper proposes a power allocation scheme to maximize the sum capacity of all users for signal‐to‐leakage‐and‐noise ratio (SLNR) precoded multiuser multiple‐input single‐output downlink. The designed scheme tries to explore the effect of the power allocation for the SLNR precoded multiuser multiple‐input single‐output system on sum capacity performance. This power allocation problem can be formulated as an optimization problem. With high signal‐to‐interference‐plus‐noise ratio assumption, it can be converted into a convex optimization problem through the geometric programming and hence can be solved efficiently. Because the assumption of high signal‐to‐interference‐plus‐noise ratio cannot be always satisfied in practice, we design a globally optimal solution algorithm based on a combination of branch and bound framework and convex relaxation techniques. Theoretically, the proposed scheme can provide optimal power allocation in sum capacity maximization. Then, we further propose a judgement‐decision algorithm to achieve a trade‐off between the optimality and computational complexity. The simulation results also show that, with the proposed scheme, the sum capacity of all the users can be improved compared with three existing power allocation schemes. Meanwhile, some meaningful conclusions about the effect of the further power allocation based on the SLNR precoding have been also acquired. The performance improvement of the maximum sum capacity power allocation scheme relates to the transmit antenna number and embodies different variation trends in allusion to the different equipped transmit antenna number as the signal‐to‐noise ratio (SNR) changes.Copyright © 2013 John Wiley & Sons, Ltd.     

Energy‐Efficiency Power Allocation for Cognitive Radio MIMO‐OFDM Systems

This paper studies energy‐efficiency (EE) power allocation for cognitive radio MIMO‐OFDM systems. Our aim is to minimize energy efficiency, measured by “Joule per bit” metric, while maintaining the minimal rate requirement of a secondary user under a total power constraint and mutual interference power constraints. However, since the formulated EE problem in this paper is non‐convex, it is difficult to solve directly in general. To make it solvable, firstly we transform the original problem into an equivalent convex optimization problem via fractional programming. Then, the equivalent convex optimization problem is solved by a sequential quadratic programming algorithm. Finally, a new iterative energy‐ efficiency power allocation algorithm is presented. Numerical results show that the proposed method can obtain better EE performance than the maximizing capacity algorithm.     

Downlink resource allocation in multi-carrier systems: frequency-selective vs. equal power allocation

This paper revisits equal power allocation from the viewpoint of asymptotic network utility maximization (NUM) problem in multi-carrier systems. It is a well-known fact that the equal power allocation is near optimal to the sum capacity maximization problem in high SNR (Signal-to-Noise Ratio) regime, i.e., optimal water-filling approximates to equal power allocation in that case. Due to this property together with its simplicity, the equal power allocation has been adopted in several researches, but its performance in other problems has not been clearly understood. We evaluate the suitability of equal power allocation in NUM problem which turns into various resource sharing policies according to utility functions. Namely, our conclusion is that in frequency selective channels, the equal power allocation is near optimal for efficiency-oriented resource sharing policy, but when fairness is emphasized, its performance is severely degraded and thus frequency-selective power allocation is necessary. For this, we develop a suboptimal subcarrier and frequency-selective power allocation algorithm for asymptotic NUM problem using the gradient-based scheduling theory and compare the performance of equal power allocation and the developed algorithm. Extensive simulation results are presented to verify our arguments.     

Decentralized beamforming design and power allocation for limited coordinated multi-cell network

Multi-cell processing （MCP） is capable of providing significant performance gain, but this improvement is accompanied by dramatic signaling overhead between cooperative base stations. Therefore, balancing the performance gain and overhead growth is crucial for a practical multi-base cooperation scheme. In this paper, we propose a decentralized algorithm to jointly optimize the power allocation and beamforming vector with the goal of maximizing the system performance under the constraint of limited overhead signal and backhaul link capacity. In particular, combined with calculating the transmission beamforming vector according to the local channel state information, an adaptive power allocation is presented based on the result of sum capacity estimation. Furthermore, by utilizing the concept of cell clustering, the proposed framework can be implemented in a practical cellular system without major modification of network architecture. Simulation results demonstrate that the proposed scheme improves the system performance in terms of the sum capacity and cell-edge capacity.     

Optimal Resource Allocation Scheme in a Multirate Overlapped Optical CDMA System

This paper addresses the problem of resource allocation in a multiservice optical network based on an overlapped code-division-multiple-access system. A joint transmission power and overlapping coefficient (transmission rate) allocation strategy is provided via the solution of a constrained convex quadratic optimization problem. The solution of this problem maximizes the aggregate throughput subject to peak laser transmission power constraints. The optimization problem is solved in a closed form, and the resource allocation strategy is simple to implement in an optical network. Simulation results are presented, showing a total agreement between the derived analytical solution and the one obtained using a numerical search method. In addition, analytical and numerical results show that the proposed resource allocation strategy can offer substantial improvement in the system throughput.     

Resource Allocation for Decode-and-Forward Relaying Assisted Multi-cell Orthogonal Frequency Division Multiplexing Systems with Frequency Planning

In this paper we apply frequency planning to the resource allocation of multi-cell and multi-user relay enhanced orthogonal frequency division multiplexing systems and propose a low-complexity algorithm taking into account of interference coordination, subcarrier and power allocation. We divide each cell into three sectors and allow different subcarrier set that can be used by the users of one sector. Such a method can help to increase the distance among users that use the same subcarriers of adjacent cells, which can reduce the impact of co-channel interference to a certain extent. Therefore, the original problem can be decoupled into three independent sub-problems by means of frequency dividing and adaptive power allocation at base station nodes which can reduce the computing complexity greatly. In the process of resource allocation for single sector, the relationship of transmission power between base station and relay node is used to transform the max-min problem into standard closed expression. With the help of dual decomposition approach, water-filling theorem and iterative power allocation algorithm, the suboptimal solution of the primal problem can be achieved finally. Simulation results illustrate that our proposed algorithm achieves almost the same performance as the optimal resource allocation and reduce the computing complexity greatly. In addition, the proposed algorithm can ensure the users fairness of different sectors.     

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 Cognitive Radio (CR) based on convex optimization theory. Then, because of high complexity of the optimal 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.     

Design and Analysis of MIMO Spatial Multiplexing Systems With Quantized Feedback

This paper investigates the problem of transmit beamforming in multiple-antenna spatial multiplexing (SM) systems employing a finite-rate feedback channel. Assuming a fixed number of spatial channels and equal power allocation, we propose a new criterion for designing the codebook of beamforming matrices that is based on minimizing an approximation to the capacity loss resulting from the limited rate in the feedback channel. Using the criterion, we develop an iterative design algorithm that converges to a locally optimum codebook. Under the independent identically distributed channel and high signal-to-noise ratio (SNR) assumption, the effect on channel capacity of the finite-bit representation of the beamforming matrix is analyzed. Central to this analysis is the complex multivariate beta distribution and tractable approximations to the Voronoi regions associated with the code points. Furthermore, to compensate for the degradation due to the equal power allocation assumption, we propose a multimode SM transmission strategy wherein the number of data streams is determined based on the average SNR. This approach is shown to allow for effective utilization of the feedback bits resulting in a practical and efficient multiple-input multiple-output system design.     

一种多中继协作系统中的功率分配算法

提出了多中继无线通信系统的模型,研究其源节点和各中继节点间功率分配对系统容量的影响,在总功率一定的情况下,探讨了以容量最大化为准则的功率分配算法。对采用非再生协作中继方式的多中继协作通信系统进行了容量分析,并提出了一种低复杂度的最优功率分配算法(Optimum Power Allocation,OPA)。仿真结果表明,该算法相对于平均功率分配算法(Average Power Allocation,APA),系统容量得到了显著提高,在信道条件差的情况下,性能提高更明显。     

Optimal simultaneous wireless information and energy transfer in OFDMA decode-and-forward relay networks

In this paper, we consider simultaneous wireless information and energy transfer in an orthogonal-frequency-division-multiple-access decode-and-forward relay network, in which an energy-constrained relay node harvests energy from a source node and uses the harvested energy to forward information to multiple destination nodes. Our objective is to maximize the end-to-end sum rate by resource allocation, subject to transmit power constraint at the source and energy-harvesting (EH) constraint at the relay. A non-convex and mixed-integer programming (MIP) problem is formulated to optimize time-switching (TS) ratios of EH and information decoding at the relay, TS ratio of information transmission from relay to destinations, subcarrier allocation as well as power allocation (PA) over all subcarriers at source and relay. We propose to decouple this problem into a convex problem and an MIP problem in fractional form. To solve the MIP problem, we transform it into an equivalent optimization problem in subtractive form which has a tractable solution. As a result, we propose a novel scheme to achieve jointly optimal TS ratios, subcarrier allocation and PA. Simulation results verify the optimality of our proposed resource allocation scheme.     

Optimal power allocation for cognitive radio under interference outage constraint

Cognitive radio is able to share the spectrum with primary licensed user, which greatly improves the spectrum efficiency. We study the optimal power allocation for cognitive radio to maximize its ergodic capacity under interference outage constraint. An optimal power allocation scheme for the secondary user with complete channel state information is proposed and its approximation is presented in closed form in Rayleigh fading channels. When the complete channel state information is not available, a more practical transmitter-side joint access ratio and transmit power constraint is proposed. The new constraint guarantees the same impact on interference outage probability at primary user receiver. Both the optimal power allocation and transmit rate under the new constraint are presented in closed form. Simulation results evaluate the performance of proposed power allocation schemes and verify our analysis.     

Rate, Sub-Carrier, and Power Allocations for Multi-Carrier CDMA with LMMSE Multiuser Detection

Multi-carrier code-division-multiple-access (MC-CDMA) is a promising transmission technique for high-speed wireless multimedia communication in frequency-selective fading channels. In this letter, allocations of physical transmission rate, sub-carrier, and power are proposed for a MC-CDMA system that applies multi-code (MC)/variable-spreading-length (VSL) multi-rate access to minimize total transmitted power, where we consider users have different data rate and BER.requirements and LMMSE multiuser detection is used in the receivers. We derive transmission rate capacity and propose a simple admission control criterion that linearly relates the code length, data rate and BER requests of all users. The proposed iterative allocation algorithm jointly allocates the sub-carrier power of each user and solves the sub-carrier allocation problem     

On co-channel and adjacent channel interference mitigation in cognitive radio networks

Cognitive radio (CR) is an emerging wireless communications paradigm of sharing spectrum among licensed (or, primary) and unlicensed (or, CR) users. In CR networks, interference mitigation is crucial not only for primary user protection, but also for the quality of service of CR user themselves. In this paper, we consider the problem of interference mitigation via channel assignment and power allocation for CR users. A cross-layer optimization framework for minimizing both co-channel and adjacent channel interference is developed; the latter has been shown to have considerable impact in practical systems. Cooperative spectrum sensing, opportunistic spectrum access, channel assignment, and power allocation are considered in the problem formulation. We propose a reformulation–linearization technique (RLT) based centralized algorithm, as well as a distributed greedy algorithm that uses local information for near-optimal solutions. Both algorithms are evaluated with simulations and are shown quite effective for mitigating both types of interference and achieving high CR network capacity.