An opportunistic resource allocation approach for mixed QoS and non-QoS connections in OFDMA wireless networks

An opportunistic resource allocation approach is proposed to guarantee both fair resource allocation and high system throughput under combinations of QoS and non-QoS connections in OFDMA networks. This approach features dynamic connection classification and packet prioritization based on real-time network conditions and QoS constraints. A classifier is first employed to prioritize QoS connections by observing the channel state of each subscriber station and the utilization of network resources. It performs a finite-horizon Markov decision process with dynamic rules affected by system load. The transmission order of packets is then determined by an opportunistic multiservice scheduler according to the QoS requirements of connections and the output of the classifier. Having the scheduling result, an allocator assigns slots to the scheduled packets, and its output is linked back to the connection classifier through a resource usage observer for all subscriber stations. The sub-channel allocation problem is also solved by cooperation between the slot allocator and the packet scheduler. Results of numerical analysis and NS2 simulation confirm the advantages claimed above. The same conclusion can also be drawn from the comparison with several existing approaches in terms of system throughput, service successful ratio, average spectral efficiency, and system revenue.     

A CDMA/TDD approach for wireless mesh networks

Wide band mesh or star oriented networks have recently become a subject of greater interest. Providing wideband multimedia access for a variety of applications has led to the inception of mesh networks. Classic access techniques such as FDMA and TDMA have been the norm for such networks. CDMA maximum transmitter power is much less than TDMA and FDMA counter parts, which is an important asset for mobile operation. In this paper we introduce a code division multiple access/time division duplex technique CDMA/TDD for such networks. The CDMA approach is an almost play and plug technology for wireless access, making it amenable for implementation by the mesh network service station, SS. Further it inherently allows mesh network service stations to use a combination of turbo coding and dynamic parallel orthogonal transmission to improve network efficiency. We outline briefly the new transmitter and receiver structures then evaluate the efficiency, delay and delay jitter. By analysis we show the advantages over classic counter parts with respect to the total network efficiency achievable especially for larger number of hops.     

Energy-efficient resource allocation in future wireless networks by sequential fractional programming

This overview paper discusses the framework of sequential fractional programming for energy efficiency maximization in future 5G networks. One of the main features of future systems will be the presence of severe multi-user interference and the need of improved energy efficiency compared to present systems. However, present approaches to energy efficiency maximization, which are based on the theory of fractional programming, result in an exponential complexity in interference-limited networks. In this context, the work shows how to extend available fractional programming approaches to obtain radio resource allocations enjoying strong optimality properties, while at the same time requiring an affordable complexity to be computed. The resulting framework is termed sequential fractional programming, and several examples of its applications to leading 5G candidate technologies are discussed in detail.     

A fair resource allocation protocol for multimedia wireless networks

Wireless networks are expected to support real-time interactive multimedia traffic and must be able, therefore, to provide their users with quality-of-service (QoS) guarantees. Although the QoS provisioning problem arises in wireline networks as well, mobility of hosts and scarcity of bandwidth makes QoS provisioning a challenging task in wireless networks. It has been noticed that multimedia applications can tolerate and gracefully adapt to transient fluctuations in the QoS that they receive from the network. The additional flexibility afforded by the ability of multimedia applications to tolerate and adapt to transient changes in QoS can be exploited by protocol designers to significantly improve the overall performance of wireless systems. This paper presents a fair resource allocation protocol for multimedia wireless networks that uses a combination of bandwidth reservation and bandwidth borrowing to provide network users with QoS in terms of guaranteed bandwidth, call blocking, and call dropping probabilities. Our view of fairness was inspired by the well-known max-min fairness allocation protocol for wireline networks. Simulation results are presented that compare our protocol to similar schemes.     

Game Theoretic subcarrier and power allocation for wireless OFDMA networks

This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s payoff as a function of the achieved data-rate.The fairness resource allocation problem can then be modeled as a cooperative bargaining game.The objective of the game is to maximize the aggregate payoffs for the users.To search for the Nash bargaining solution(NBS) of the game,a suboptimal subcarrier allocation is performed by assuming an equal power allocation.Thereafter,an optimal power allocation is performed to maximize the sum payoff for the users.By comparing with the max-rate and the max-min algorithms,simulation results show that the proposed game could achieve a good tradeoff between the user fairness and the overall system performance.     

Time-aware utility-based resource allocation in wireless networks

This paper presents a time-aware admission control and resource allocation scheme in wireless networks in the context of a future generation cellular network. The quality levels (and their respective utility) of different connections are specified using discrete resource-utility (R-U) functions. The scheme uses these R-U functions for allocating and reallocating bandwidth to connections, aiming to maximize the accumulated utility of the system. However, different applications react differently to resource reallocations. Therefore, at each allocation time point, the following factors are taken into account: the age of the connection, a disconnection (drop) penalty, and the sensitiveness to reallocation frequency. The evaluation of our approach shows a superior performance compared to a recent adaptive bandwidth allocation scheme (RBBS). In addition, we have studied the overhead that performing a reallocation imposes on the infrastructure. To minimize this overhead, we present an algorithm that efficiently reduces the number of reallocations while remaining within a given utility bound.     

一种容量最大化的OFDMA资源分配算法

针对功率受限的多用户OFDMA系统,提出了一种简化的子载波和功率分配算法,此算法在最大化系统容量的同时兼顾了用户间的公平性。算法首先依据当前的信道状况计算出各用户所需的载波数量,并分配子载波,然后以注水算法对各载波上的功率进行分配。仿真结果表明,以此算法对OFDMA的系统资源进行分配可显著提高系统的多项性能。     

中继OFDMA系统用户公平性的资源分配算法的研究

在OFDMA解码—转发中继系统中,为了公平地进行资源分配,提出了在两个用户模型下,在保证每个用户最小速率需求的前提下,先按照用户预定速率比进行子载波分配,再根据实际速率比对用户的子载波进行调整的分配算法,最后使整个系统的吞吐量达到最大。提出了三种方案。方案一通过对Lagrange对偶函数问题的求解,根据所得代价函数值的大小对用户的子载波做重新调整。这样不仅考虑到了公平性,也减少了用户的速率损失。方案二、方案三分别从子载波端和用户端出发考虑子载波的分配问题,且从不同的分配角度分析了公平性问题。研究结果表明,三种方案获得的公平性均有所提高。     

基于效用函数的OFDM混合业务资源调度算法*

主要研究了QoS和BE两种混合业务场景下OFDM无线网络下行链路的资源调度问题,提出了一个基于效用函数的跨层资源调度模型,其能够自适应地对两种业务进行资源的联合优化分配。该模型被抽象为一个非线性整数规划问题,优化目标是系统总效用最大化,同时满足同信道干扰（CCI）约束以及QoS业务的质量要求。将该非线性整数规划问题转换为连续松弛凸规划问题进行求解,并结合最优松弛解,提出了一种简单的动态子载波分配算法,即MMU(mix-max-utility) 算法。仿真结果验证了该调度算法能使系统较好地支持混合业务,系统     

Interference aware resource allocation for hybrid hierarchical wireless networks

This paper addresses the problem of interference aware resource allocation for OFDMA based hybrid hierarchical wireless networks. We develop two resource allocation algorithms considering the impact of wireless interference constraints using a weighted SINR conflict graph to quantify the interference among the various nodes: (1) interference aware routing using maximum concurrent flow optimization; and (2) rate adaptive joint subcarrier and power allocation algorithm under interference and QoS constraints. We exploit spatial reuse to allocate subcarriers in the network and show that an intelligent reuse of resources can improve throughput while mitigating interference. We provide a sub-optimal heuristic to solve the rate adaptive resource allocation problem. We demonstrate that aggressive spatial reuse and fine tuned-interference modeling garner advantages in terms of throughput, end-to-end delay and power distribution.     

基于深度Q学习的室内无线网络资源分配算法

针对室内无线网络中的能量消耗过大问题,提出了一种基于深度Q学习的家庭基站发射功率分配算法.首先构造深度学习网络(DLN),优化室内无线网络的能量效率;然后将能量消耗指数作为奖罚值,利用批量梯度下降法不断地训练DLN的权值.最后仿真结果表明,所提出的算法可以动态调整发射功率,在收敛速度和能量消耗优化方面明显优于Q学习算法...     

基于能效的OFDMA系统资源分配研究*

在正交频分多址（OFDMA）系统中,合理的资源分配对于提升系统的能效具有重要的意义。针对多用户OFDMA系统,对最大化系统能效为目标的资源分配算法进行研究,提出了基于智能水滴算法的全连通图资源分配模型,该模型以全连通图的顶点和边来表示用户与子载波之间的对应关系。在此基础上,进一步对智能水滴算法进行改进。仿真结果表明,在满足用户QoS的条件下,所提出的改进的智能水滴算法的全连通图资源分配方案能够有效提高系统能效,提升系统性能。     

Energy-efficient dynamic resource allocation with opportunistic network coding in OFDMA relay networks

Network coding is significantly able to save system resources for wireless networks, and has been widely studied for the 802.11 wireless local area network and traditional cellular networks. The relay technology was introduced in 802.16j, 802.16m, and Long Term Evolution-Advanced (LTE-A) standards. Recently, the application of network coding to multi-hop wireless relay networks has been taken into consideration. Although the introduction of relay stations (RSs) may bring more energy consumption, it provides opportunities for network coding to save spectrum resources. Nevertheless, the benefits of network coding are diminished by high multiuser diversity based on orthogonal frequency division multiple access (OFDMA). For ensuring the superiority, network coding is performed opportunistically according to the channel state. Hence dynamic resource allocation (DRA) subject to rate constraints is combined with the idea of opportunistic network coding to minimize the total transmission power in a frame. A fixed set of discrete modulation levels in an OFDMA relay system is also considered. By taking the characteristic of a half-duplex decode-and-forward (DF) mode relay, a solution is proposed for the optimal problem of each subframe after separating power-aware relay selection. Simulation results show that DRA with opportunistic network coding can improve system energy efficiency. Further, it is more efficient for saving energy than DRA with static network coding compared solely to DRA.     

一种基于工业无线网络的路由和资源分配算法

采用家族谱系的描述方法,提出了一种适用于复杂现场监测的工业无线传感器网络路由和通信资源分配算法.该算法利用无线传感器网络的广播特性,采用分层、分时和分频相结合的策略实现路由和通信资源的分配,具有条理清晰、实现简单的特点.仿真测试表明,该算法能够有效提高无线网络的通信效率,可靠性高,并具有良好的可扩展性.     

Radio resource allocation problems for OFDMA cellular systems

Orthogonal frequency division multiple-access (OFDMA) manages to efficiently exploit the inherent multi-user diversity of a cellular system by performing dynamic resource allocation. Radio resource allocation is the technique that assigns to each user in the system a subset of the available radio resources (mainly power and bandwidth) according to a certain optimality criterion on the basis of the experienced link quality. In this paper we address the problem of resource allocation in the downlink of a multi-cellular OFDMA system. The allocation problem is formulated with the goal of minimizing the transmitted power subject to individual rate constraint for each user. Exact and heuristic algorithms are proposed for the both the single-cell and the multi-cell scenario. In particular, we show that in the single-cell scenario the allocation problem can be efficiently solved following a network flow approach. In the multi-cell scenario we assume that all cells use the same frequencies and therefore the allocation problem is complicated by the presence of strong multiple access interference. We prove that the problem is strongly NP-hard, and we present an exact approach based on an MILP formulation. We also propose two heuristic algorithms designed to be simple and fast. All algorithms are tested and evaluated through an experimental campaign on simulated instances. Experimental results show that, although suboptimal, a Lagrangian-based heuristic consisting in solving a series of minimum network cost flow problems is attractive for practical implementation, both for the quality of the solutions and for the small computational times.     

Pareto optimal time-frequency resource allocation for selfish wireless cooperative multicast networks

In selfish wireless cooperative multicast networks （WCMNs）, a source node wants to achieve the optimal benefit （i.e., rate gain）, while the relaying nodes are willing to get fairness rewards （i.e., rate gains） from the source for the cooperative relaying. In this paper, we implement these two different objectives for the source and the relays through the Pareto optimal resource allocation. Define the cooperative strategy of a node as the fraction of a data-frame that it is willing to contribute to its cooperative partners. Consider the rational decision made by one node will definitely affect its cooperative partners＇ choice. Then, we can formulate this resource sharing problem as a Nash bargaining problem （NBP）, and the Nash bargaining solution （NBS） to the NBP encapsulates the Pareto optimality naturally. Finally, to enable the nodes to be capable of computing the NBS cooperative strategies rapidly as the wireless channel changes, we propose a fast particle swarm optimizer （PSO） algorithm to search for the NBS. Simulation results show that the two specified objectives of the source and the relays can be implemented in the Pareto optimal sense, i.e., the source can achieve a significant performance gain in comparison with direct multicast and the relays can get a fair reward by the source according to the level of contribution it has made to improve the performance of the source.     

HAPS通信中的低复杂度OFDMA资源分配策略

针对配置于高空平台(HAPS)的OFDMA系统,研究了在平台功率受限情况下的资源分配问题。采用对偶理论,推导了在连续情况下,最小化发送功率时,OFDMA载波、功率、速率分配的最优解,同时利用统计近似法实现算法的实时配置。仿真结果表明,该算法性能与经典C.Y.Wong算法性能大致相同,而算法复杂度仅为线性复杂度,具有较强的实际应用价值。     

JCCA resource allocation for video transmission in relay-enhanced OFDMA system

Resulting from the rapid growth of wireless video services in the recent years, radio resource is often inadequate in the high data rate communication environment. Under the circumstance, it is important to make full use of limited resource for efficient video transmission. Hence, we propose a joint content and channel aware (JCCA) resource allocation algorithm in relay-enhanced OFDMA system. It can maximize accumulation of allocated subcarriers’ contribution for transmitting video data so as to improve overall quality of users’ received video under resource constrained conditions. As it is described in this work, the algorithm is implemented by packet scheduling, path selection and subcarrier allocation, in which time-varying data content and channel state are jointly considered at the same time. And the two implementation schemes, JCCAG and JCCAL, are designed for JCCA resource allocation algorithm. JCCAG is executed for allocating subcarriers through global search among all subcarriers’ contribution. For reducing complexity of JCCAG, subcarriers are allocated according to the corresponding contribution towards each user on the basis of local search in JCCAL. In the simulation, we make comparison between the JCCA resource allocation algorithm and others for video transmission in relay-enhanced OFDMA system. And the comparison results are evaluated through objective and subjective criterion, respectively. It is demonstrated that the proposed algorithm can perform better in improving overall quality of users’ received video.     

Dynamic radio resource allocation for 3G and beyond mobile wireless networks

Next generation of wireless cellular networks aim at supporting a diverse range of multimedia services to mobile users with guaranteed quality of service (QoS). Resource allocation and call admission control (CAC) are key management functions in future 3G and 4G cellular networks, in order to provide multimedia applications to mobile users with QoS guarantees and efficient resource utilization. There are two main strategies for radio resource allocations in cellular wireless networks known as complete partitioning (CP) and complete sharing (CS). In this paper, theses strategies are extended for operation in 3G and beyond network. First, two CS-based call admission controls, referred to herein as queuing priority call admission control (QP-CAC) and hybrid priority call admission control (HP-CAC), and one CP-based call admission control referred to as complete partitioning call admission control (CP-CAC) are presented. Then, this study proposes a novel dynamic procedure, referred to as the dynamic prioritized uplink call admission control (DP-CAC) designed to overcome the shortcomings of CS and CP-based CACs. Results indicate the superiority of DP-CAC as it is able to achieve a better balance between system utilization, revenue, and quality of service provisioning. CS-based algorithms achieve the best system utilization and revenue at the expense of serious unfairness for the traffic classes with diverse QoS requirements. DP-CAC manages to attain equal system utilization and revenue to CS-based algorithms without the drawbacks in terms of fairness and service differentiation.     

A dynamic programming approach: Improving the performance of wireless networks

Traditional wireless networks focus on transparent data transmission where the data are processed at either the source or destination nodes. In contrast, the proposed approach aims at distributing data processing among the nodes in the network thus providing a higher processing capability than a single device. Moreover, energy consumption is balanced in the proposed scheme since the energy intensive processing will be distributed among the nodes. The performance of a wireless network is dependent on a number of factors including the available energy, energy–efficiency, data processing delay, transmission delay, routing decisions, security architecture etc. Typical existing distributed processing schemes have a fixed node or node type assigned to the processing at the design phase, for example a cluster head in wireless sensor networks aggregating the data. In contrast, the proposed approach aims to virtualize the processing, energy, and communication resources of the entire heterogeneous network and dynamically distribute processing steps along the communication path while optimizing performance. Moreover, the security of the communication is considered an important factor in the decision to either process or forward the data. Overall, the proposed scheme creates a wireless “computing cloud” where the processing tasks are dynamically assigned to the nodes using the Dynamic Programming (DP) methodology. The processing and transmission decisions are analytically derived from network models in order to optimize the utilization of the network resources including: available energy, processing capacity, security overhead, bandwidth etc. The proposed DP-based scheme is mathematically derived thus guaranteeing performance. Moreover, the scheme is verified through network simulations.