Proportional Fairness-Based Power Allocation Algorithm for Downlink NOMA 5G Wireless Networks

Non-orthogonal multiple access (NOMA) is one of the key 5G technology which can improve spectrum efficiency and increase the number of user connections by utilizing the resources in a non-orthogonal manner. NOMA allows multiple terminals to share the same resource unit at the same time. The receiver usually needs to configure successive interference cancellation (SIC). The receiver eliminates co-channel interference (CCI) between users and it can significantly improve the system throughput. In order to meet the demands of users and improve fairness among them, this paper proposes a new power allocation scheme. The objective is to maximize user fairness by deploying the least fairness in multiplexed users. However, the objective function obtained is non-convex which is converted into convex form by utilizing the optimal Karush-Kuhn-Tucker (KKT) constraints. Simulation results show that the proposed power allocation scheme gives better performance than the existing schemes which indicates the effectiveness of the proposed scheme.     

An Adaptive Power Allocation Scheme for Performance Improvement of Cooperative SWIPT NOMA Wireless Networks

Future wireless networks demand high spectral efficiency, energy efficiency and reliability. Cooperative non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer (SWIPT) is considered as one of the novel techniques to meet this demand. In this work, an adaptive power allocation scheme called SWIPT based adaptive power allocation (SWIPT-APA-NOMA) is proposed for a power domain NOMA network. The proposed scheme considers the receiver sensitivity of the end users while calculating the power allocation coefficients in order to prevent wastage of power allocated to user in outage and by offering priority to any one of the users to use maximum harvested power. A detailed analysis on the bit error rate (BER) performance of the proposed scheme is done and closed form expression is obtained. Simulations have been carried out with various parameters that influence the receiver sensitivity and the results show that the network achieves better outage and BER performance using the proposed scheme. It is found that the proposed scheme leads to a ten-fold decrease in transmit power for the same error performance of a fixed power allocation scheme. Further, it offers 96.06% improvement in the capacity for a cumulative noise figure and fading margin of 10 dB.     

Energy Efficient Resource Allocation Approach for Renewable Energy Powered Heterogeneous Cellular Networks

In this paper, maximizing energy efficiency (EE) through radio resource allocation for renewable energy powered heterogeneous cellular networks (HetNet) with energy sharing, is investigated. Our goal is to maximize the network EE, conquer the instability of renewable energy sources and guarantee the fairness of users during allocating resources. We define the objective function as a sum weighted EE of all links in the HetNet. We formulate the resource allocation problem in terms of subcarrier assignment, power allocation and energy sharing, as a mixed combinatorial and non-convex optimization problem. We propose an energy efficient resource allocation scheme, including a centralized resource allocation algorithm for iterative subcarrier allocation and power allocation in which the power allocation problem is solved by analytically solving the Karush-Kuhn-Tucker (KKT) conditions of the problem and a water-filling problem thereafter and a low-complexity distributed resource allocation algorithm based on reinforcement learning (RL). Our numerical results show that both centralized and distributed algorithms converge with a few times of iterations. The numerical results also show that our proposed centralized and distributed resource allocation algorithms outperform the existing reference algorithms in terms of the network EE.     

Outage Capacity Analysis for Cognitive Non-Orthogonal Multiple Access Downlink Transmissions Systems in the Presence of Channel Estimation Error

In this paper, we propose a downlink cognitive non-orthogonal multiple access (NOMA) network, where the secondary users (SUs) operate in underlay mode. In the network, secondary transmitter employs NOMA signaling for downlink transmission, and the primary user (PU) is interfered by the transmission from SU. The expressions for the outage probabilities are derived in closed-form for both primary and secondary users in the presence of channel estimation error. Numerical simulation results show that the channel estimation error and the inter-network interference cause degradation of the downlink outage performance. Also the power allocation and the location have a significant impact on the outage probability. The numerical experiments demonstrate that the analytic expressions of the outage probabilities match with the simulation results.     

Power control for interference mitigation by evolutionary game theory in uplink NOMA for 5G networks

The demand for mobile uplink traffic has increased significantly in the past few decades with the development of the Internet of Things (IoT) and mobile Internet. This has subsequently imposed challenges on 5G networks to provide high spectral efficiency and low-power massive connectivity. Non-orthogonal multiple access (NOMA) is a viable alternative to the current state-of-the-art orthogonal multiple access (OMA) techniques to address the challenges in 5G systems. In addition, a power control (PC) mechanism to mitigate the effect of interference between users can be accommodated to improve network performance. In this paper, we discuss the basic principles, key features, and strengths/weaknesses of the various power domain NOMA schemes. Moreover, we propose an uplink PC scheme for the users of a power domain NOMA network. The proposed PC method makes use of the evolutionary game theory (EGT) model to adaptively adjust the transmitted power level of the users which helps in mitigating user interference. A successive interference cancellation (SIC) receiver is applied at a base station (BS) in order to separate the users’ signals. By performing simulations, we show that the proposed EGT-based PC scheme achieves higher network efficiency, spectral efficiency, and energy efficiency.     

OFDM水声通信下行非正交多址接入功率分配方法研究

针对基于功率域非正交多址接入（Power Domain Non-orthogonal Multiple Accesses,PD-NOMA）的正交频分复用（Orthogonal Frequency Division Multiplexing,OFDM）水声下行通信系统的功率分配问题,提出了一种基于中断概率的功率分配方法。用户节点在系统初始化阶段根据源节点广播的组网数据包获取水声信道的统计特征,源节点根据水下用户反馈的信道特征参数建立水下用户的中断概率模型,以最小化两用户的中断概率和为目标建立目标函数,在中断概率区域边界上遍历搜索最优的功率分配系数。仿真结果表明,该方法在保证公平性的条件下,有效降低了用户节点的中断概率,提高了系统的频谱利用率和误码性能。     

Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems

Energy efficiency (EE) is a critical design when taking into account circuit power consumption (CPC) in fifth-generation cellular networks. These problems arise because of the increasing number of antennas in massive multiple-input multiple-output (MIMO) systems, attributable to inter-cell interference for channel state information. Apart from that, a higher number of radio frequency (RF) chains at the base station and active users consume more power due to the processing activities in digital-to-analogue converters and power amplifiers. Therefore, antenna selection, user selection, optimal transmission power, and pilot reuse power are important aspects in improving energy efficiency in massive MIMO systems. This work aims to investigate joint antenna selection, optimal transmit power and joint user selection based on deriving the closed-form of the maximal EE, with complete knowledge of large-scale fading with maximum ratio transmission. It also accounts for channel estimation and eliminating pilot contamination as antennas M → ∞. This formulates the optimization problem of joint optimal antenna selection, transmits power allocation and joint user selection to mitigate inter-cell-interference in downlink multi-cell massive MIMO systems under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm (LCA) for Newton’s methods and Lagrange multipliers. To analyze the precise power consumption, a novel power consumption scheme is proposed for each individual antenna, based on the transmit power amplifier and CPC. Simulation results demonstrate that the maximal EE was achieved using the iterative LCA based on reasonable maximum transmit power, in the case the noise power is less than the received power pilot. The maximum EE was achieved with the desired maximum transmit power threshold by minimizing pilot reuse, in the case the transmit power allocation ρ_d = 40 dBm, and the optimal EE = 71.232 Mb/j.     

Throughput fairness and efficiency of link adaptation techniques in wireless networks

Link adaptation techniques aim to maximise the quality of service and resource utilisation in wireless networks. However, fairness must be taken into consideration, particularly, in low-mobility environments where the channel dynamic variation is small. The authors propose and analyse three link adaptation techniques [using joint power control (PC) and adaptive coding and modulation (ACM)] for fairness enhancement. In the first technique, called aggregate throughput maximisation with fairness constraint, the authors formulate the fairness problem as a constrained optimisation problem where the authors try to maximise the aggregate throughput subject to the throughput fairness constraint. In order to solve the optimisation problem, the authors convert the constrained optimisation problem to an unconstrained optimisation one using the penalty method. Then, the unconstrained optimisation problem is solved using the steepest descent technique. The second techniques, called individual throughput balancing, tries to equalise the individual throughput by using a higher throughput level for disadvantaged users and using a lower throughput level for advantaged users. Finally, the third technique, called adaptive virtual maximum power constraint, uses virtual maximum power cap, which is lower than the real maximum power cap. The virtual maximum power cap of each user is variable and it adapts based on the user's individual throughput to compensate disadvantaged users. The authors analyse the three proposed techniques in terms of the throughput fairness and the throughput efficiency and compare them with three basic link adaptation techniques (PC, ACM, and joint PC and ACM). The three proposed techniques are shown to be able to enhance the fairness with different degrees and with different levels of aggregate throughput degradation.     

OFDMA系统资源优化综述

在正交频分多址(OFDMA)系统中,有效的资源分配可以充分发挥系统性能.目前的资源优化主要分为频谱效率优化与系统能效优化两个方面.频谱效率优化即在给定的总功率下,最大化系统总容量;系统根据信道状态信息,分步对子载波和功率进行分配.根据不同的业务需求,频谱效率优化又细分为仅考虑频谱效率的优化以及考虑用户公平性与复杂通信环境下的优化.系统能效优化是在保证系统总容量的同时,降低系统的总功率消耗.能效优化算法采用了分式规划、约束条件松弛与拉格朗日对偶分解等最优化理论的方法进行资源分配的优化.在加入不同约束的考虑下,能效优化算法分为保证用户公平性、回程线路容量、通信安全等不同的能效优化方案.但是,这两方面的资源优化对不完整信道信息的情况考虑较少,对于多业务的资源分配,未能针对业务多样性进行高效资源优化.另外,资源优化在跨层资源分配上仍有不足.     

Resource Allocation for Throughput Maximization in Cognitive Radio Network with NOMA

Spectrum resources are the precious and limited natural resources. In order to improve the utilization of spectrum resources and maximize the network throughput, this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonal multiple access (CRN-NOMA). NOMA, as the key technology of the fifth-generation communication (5G), can effectively increase the capacity of 5G networks. The optimization problem proposed in this paper aims to maximize the number of secondary users (SUs) accessing the system and the total throughput in the CRN-NOMA. Under the constraints of total power, minimum rate, interference and SINR, CRN-NOMA throughput is maximized by allocating optimal transmission power. First, for the situation of multiple sub-users, an adaptive optimization method is proposed to reduce the complexity of the optimization solution. Secondly, for the optimization problem of nonlinear programming, a maximization throughput optimization algorithm based on Chebyshev and convex (MTCC) for CRN-NOMA is proposed, which converts multi-objective optimization problem into single-objective optimization problem to solve. At the same time, the convergence and time complexity of the algorithm are verified. Theoretical analysis and simulation results show that the algorithm can effectively improve the system throughput. In terms of interference and throughput, the performance of the sub-optimal solution is better than that of orthogonal-frequency-division-multiple-access (OFDMA). This paper provides important insights for the research and application of NOMA in future communications.     

A Joint Algorithm for Resource Allocation in D2D 5G Wireless Networks

With the rapid development of Internet technology, users have an increasing demand for data. The continuous popularization of traffic-intensive applications such as high-definition video, 3D visualization, and cloud computing has promoted the rapid evolution of the communications industry. In order to cope with the huge traffic demand of today’s users, 5G networks must be fast, flexible, reliable and sustainable. Based on these research backgrounds, the academic community has proposed D2D communication. The main feature of D2D communication is that it enables direct communication between devices, thereby effectively improve resource utilization and reduce the dependence on base stations, so it can effectively improve the throughput of multimedia data. One of the most considerable factor which affects the performance of D2D communication is the co-channel interference which results due to the multiplexing of multiple D2D user using the same channel resource of the cellular user. To solve this problem, this paper proposes a joint algorithm time scheduling and power control. The main idea is to effectively maximize the number of allocated resources in each scheduling period with satisfied quality of service requirements. The constraint problem is decomposed into time scheduling and power control subproblems. The power control subproblem has the characteristics of mixed-integer linear programming of NP-hard. Therefore, we proposed a gradual power control method. The time scheduling subproblem belongs to the NP-hard problem having convex-cordinality, therefore, we proposed a heuristic scheme to optimize resource allocation. Simulation results show that the proposed algorithm effectively improved the resource allocation and overcome the co-channel interference as compared with existing algorithms.     

Fairness and throughput enhancement based resource allocation scheme for underlay cognitive radio networks

Acquiring good throughput and diminishing interference to primary users (PU) are the main objectives for secondary users in a cognitive radio (CR) network. This paper proposes a centralized subcarrier and power allocation scheme for underlay multi-user orthogonal frequency division multiplexing considering the rate loss and the interference those the PU can tolerate. The main purpose of the proposed scheme is to efficiently distribute the available subcarriers among cognitive users to enhance both the fairness and the throughput performance of the cognitive network while maintaining the QoS of primary users. Simulation results show that the proposed scheme achieves a significantly higher CR network throughput than that of the conventional interference power constraint (IPC) based schemes and provides a significantly enhanced fairness performance. Also, contrary to the conventional IPC based schemes, the proposed scheme is able to significantly increase the achieved throughput as the number of CR users increases.     

Outage-constrained capacity of spectrum-sharing channels in fading environments

Cognitive radio technology has been recently proposed for sharing and utilising the spectrum in order to satisfy the increasing demands for spectrum access. In this radio technology, secondary users may be granted access to the spectrum bands occupied by a primary user as long as the interference power, inflicted on the primary receiver as an effect of the transmission of the secondary user, is deemed unharmful. In this paper the authors assume that the successful operation of the primary user requires a minimum rate to be guaranteed by its channel for a certain percentage of time and obtain the interference-power constraint that is required to be fulfilled by the secondary user. Considering the input transmit-power constraint, on average or peak power, for the secondary user, the authors investigate the capacity gains offered by this spectrum-sharing approach when only partial channel information of the link between the secondary's transmitter and primary's receiver is available to the former. In particular, the lower bounds on the capacity of a Rayleigh flat-fading channel with two different transmission techniques, namely channel inversion and optimum rate allocation with constant power transmission, are derived. Closed-form expressions for these capacity metrics are provided, and numerical simulations are conducted to corroborate the theoretical results.     

Interference-limited resource allocation for cognitive radio in orthogonal frequency-division multiplexing networks

Efficient and fair resource allocation strategies are being extensively studied in current research in order to address the requirements of future wireless applications. A novel resource allocation scheme is developed for orthogonal frequency-division multiplexing (OFDM) networks designed to maximise performance while limiting the received interference at each user. This received interference is in essence used as a fairness metric; moreover, by defining different interference tolerances for different sets of users, the proposed allocation scheme can be exploited in various cognitive radio scenarios. As applied to the scheme, the authors investigate a scenario where two cellular OFDM-based networks operate as primary and secondary systems in the same band, and the secondary system benefits by accessing the unused resources of the primary system if additional capacity is required. The primary system benefits either by charging the secondary system for the use of its resources or by some form of reciprocal arrangement allowing it to use the secondary system's licenced bands in a similar manner, when needed. Numerical results show our interference-limited scheduling approach to achieve excellent levels of efficiency and fairness by allocating resources more intelligently than proportional fair scheduling. A further important contribution is the application of sequential quadratic programming to solve the non-convex optimisation problems which arise in such scenarios.     

一种新颖的多用户OFDM资源分配算法

在多用户正交频分复用(OFDM)系统中设计一种新颖的子载波-功率分配方法来最大化用户数据传输速率.这个方案分成两部分,子载波分配和功率分配.其中,子载波分配方法是在信道容量矩阵中将信道容量最好的子载波首先进行分配,功率分配采用注水方法.研究和模拟结果表明,该算法在只改变各个子载波增益系数的基础上,基本保持了较低的复杂度,并且极大地提高了用户数据传输速率.     

Joint power allocation and relay positioning in multi-relay cooperative systems

The authors consider a dual-hop multi-relay cooperative relay system in this study. Both decode-and-forward (DF) and amplify-and-forward (AF) protocols are considered. Under different relay selection strategies, the authors derive closed-form outage probability expressions. With the second-order channel statistics, the authors propose to jointly optimise power allocation (PA) and relay positions in order to minimise the system outage probability. Simulation results show that the proposed adaptive allocation algorithms significantly outperform fixed allocation algorithms. With the proposed joint optimisation algorithm, AF relaying outperforms DF relaying when multiple relays are selected to help. When only the best relay is selected to help, DF relaying is shown to have better performance.     

Capacity analysis for a multiuser cross-layer downlink model in the presence of fading and interference

A system model that employs beamforming at the physical (PHY) layer and different scheduling algorithms at the medium access control (MAC) layer is used in a downlink environment where two users are served simultaneously. The effect of the scheduling algorithms on the system performance is assessed in terms of total system capacity. The scheduling algorithms considered, choose users either randomly, or on the basis of their instantaneous signal-to-noise ratio (SNR) and/or their angular location around the base station. A semi-analytical framework for the capacity analysis is also presented. The results obtained from the numerical model are shown to be consistent with those based on the semi-analytical framework. It is shown that explicitly taking into consideration at the MAC layer the angular location of mobile users around the base station along with instantaneous SNR for the selection of users that are served simultaneously leads to an improved system capacity. This improvement is the result of reduced interference that simultaneously served users cause on each other. The results show that joint addressing of the PHY and MAC layer issues in an integrated cross-layer framework is important for achieving maximal system performance     

基于预期容量损失的OFDMA子载波分配算法

针对正交频分多址接入(OFDMA)系统的子载波分配问题,提出了一种基于预期容量损失的分配算法,该算法将子载波的联合分配分解为逐次分配以降低复杂度.每次分配时,该算法利用多用户频率选择性信道的特性,将用户在不同子载波上的速率差值作为每次分配中预期容量损失的度量,优先对预期容量损失最大的用户分配子载波,以期避免由逐次分配的非最优性导致的系统容量损失.理论分析和仿真结果表明,此算法能够在低复杂度的条件下得到近似最优解,在保证用户服务质量的同时,有效地提高了系统容量.     

Adaptive opportunistic fair scheduling in power-controlled code division multiple access systems

The authors treat the multiuser scheduling problem for practical power-controlled code division multiple access (CDMA) systems under the opportunistic fair scheduling (OFS) framework. OFS is an important technique in wireless networks to achieve fair and efficient resource allocation. Power control is an effective resource management technique in CDMA systems. Given a certain user subset, the optimal power control scheme can be derived. Then the multiuser scheduling problem refers to the optimal user subset selection at each scheduling interval to maximise certain metric subject to some specific physical-layer constraints. The authors propose discrete stochastic approximation algorithms to adaptively select the user subset to maximise the instantaneous total throughput or a general utility. Both uplink and downlink scenarios are considered. They also consider the time-varying channels where the algorithm can track the time-varying optimal user subset. Simulation results to show the performance of the proposed algorithms in terms of the throughput/ utility maximisation, the fairness, the fast convergence and the tracking capability in time-varying environments are presented.     

Adaptive subchannel allocation in multiuser multicarrier systems

The problem of multiuser scheduling in multicarrier (MC) systems under practical physical-layer constraints and implementations is considered. Subchannel allocation is an important resource assignment issue in multiuser MC systems. The multiuser scheduler is decoupled into a multiuser selector and a subchannel allocator, which result in a sub-optimum multiuser scheduler with significantly reduced computational complexity. Given an active user subset and a channel set, the multiuser scheduling problem then refers to the optimal subchannel allocation to maximise the instantaneous system throughput subject to certain fairness constraints. Efficient adaptive algorithms are developed for optimal subchannel allocation. The extension of the algorithms for tracking the time-varying optimum, which occurs in non-stationary environments, is also addressed. Simulation results are presented to demonstrate the performance of the proposed algorithms in terms of the throughput maximisation, the fast convergence, the excellent tracking capability in time-varying environments, the achievable throughput of the proposed multiuser scheduler as well as the long-term fairness