A green scheduling with adaptive spatial division multiple access grouping for multi‐user coordinated multi‐point networks

Multi‐User Coordinated Multi‐Point (MU‐CoMP), which couples CoMP with Multi User‐Multiple Input Multiple Output (MU‐MIMO), appears as a promising solution to enhance the Long Term Evolution‐Advanced (LTE‐A) system performance. However, some challenging issues in MU‐CoMP networks require more investigation. First, the set of users transmitting under CoMP mode should be properly identified. Secondly, time‐frequency resource should be efficiently partitioned between CoMP and non‐CoMP users in order to improve the system radio capacity. Thirdly, a fair and green scheduler is much needed for a more energy efficient system. This paper deals with these three issues. We propose an adaptive transmission mode selection according to the total load in the cluster and to users' quality of service. The adequate size of the Spatial Division Multiple Access users' groups is also analyzed. We finally propose a new scheduling algorithm to further enhance the radio capacity and the energy consumption in the cluster. Simulations results showed that significant improvements are obtained in terms of total system throughput and outage probability in the cluster with our proposed scheme. Moreover, energy efficiency has increased by four times with our proposed scheduling algorithm as compared to commonly used schedulers. Copyright © 2015 John Wiley & Sons, Ltd.     

Joint Downlink Scheduling and Radio Resource Allocation for User-Individual QoS in Adaptive OFDMA Wireless Communication Systems

1Introduction Futurewirelessandmobilecommunicationsystems areexpectedtoofferhigherdatarates,tosupporta largenumberofsubscribersandtoensurethefulfillment ofQualityofService(QoS)requirements,giventhe limitedavailabilityoffrequencyspectrumandtimevary ingchan…     

A dynamic paging scheme for long‐term evolution mobility management

In long‐term evolution, the service area is partitioned into several tracking areas (TAs), which comprise one or more cells (the radio coverages of base stations). The TAs are grouped into TA list (TAL). When an incoming call arrives, the network attempts to connect to the user equipment (UE) by paging the cells in the UE's TAL, which may incur large paging traffic that significantly consumes the limited radio resources. To resolve this issue, this paper proposes a dynamic paging scheme that determines the paging sequence of cells in real time according to the UE movement and call behavior. We compare the performance of the dynamic paging with that of the previously proposed Cell‐TA‐TAL (CTT) paging. Our study indicates that the dynamic paging outperforms the CTT paging when movement pattern is regular and the UE moves frequently. Copyright © 2013 John Wiley & Sons, Ltd.     

DCLRRA: Distributed cross‐layer routing and resource allocation techniques for OFDMA‐based broadband wireless networks

In this study, we develop a fully distributed routing protocol for OFDMA‐based multihop broadband wireless access (BWA) networks such as those of IEEE 802.16j. We refer to this protocol as the DCLRRA protocol. DCLRRA is based on autonomous resource allocation schemes that we also derive in this paper. The routing protocol's selection of the proper resource allocation scheme is based on whether the relay stations (RSs) are nomadic or stationary. While we develop the autonomous resource allocation schemes, we exploit the multi‐user capabilities of the OFDMA physical layer. This allows simultaneous data transmission sessions within the same neighborhood while offering a total elimination of interference between transmitting nodes. The direct result of this strategy is increased throughput with high utilization of the communication channel. We examine our routing technique to show its performance merits through extensive simulations. Copyright © 2010 John Wiley & Sons, Ltd.     

An Adaptive Hot‐Spot Operating Scheme for OFDMA Downlink Systems in Vertically Overlaid Cellular Architecture

In vertically overlaid cellular systems, a temporary traffic concentration can occur in a hot‐spot area, and this adversely affects overall system capacity. In this paper, we develop an adaptive hot‐spot operating scheme (AHOS) to mitigate the negative effects from the nonuniform distribution of user location and the variation in the mixture of QoS requirements in orthogonal frequency division multiple access downlink systems. Here, the base station in a macrocell can control the operation of picocells within the cell, and turns them on or off according to the system overload estimation function. In order to determine whether the set of picocells is turned on or off, we define an AHOS gain index that describes the number of subcarriers saved to the macrocell by turning a specific picocell on. For initiating the picocell OFF procedure, we utilize the changes in traffic concentration and co‐channel interference to the neighboring cells. According to computer simulation, the AHOS has been proved to have maximize system throughput while maintaining a very low QoS outage probability under various system scenarios in both a single‐cell and multi‐cell environments.     

Nash bargaining solution based joint time‐frequency‐code‐power resource management algorithm for TD‐LTE systems

This paper presents a joint time‐frequency‐code‐power resource management algorithm based on the Nash bargaining solution in time‐division long term evolution systems. First, a joint radio resource allocation scheme at the time, frequency, code and power domain simultaneously is provided for the time‐division long term evolution system. Second, the proposed algorithm is modeled as a cooperative game under the constraints of each user's minimal rate requirement and available resources, for example, the maximal transmitting power. To reduce the computational complexity, the joint resource allocation algorithm is divided into time‐frequency‐code and power domain resource allocation. Also, we could approach the Pareto optimal rate as closely as possible by iterations. Simulation results show that compared with the other resource allocation algorithms, the proposed algorithm has achieved a good tradeoff between the overall system throughput and fairness among different users. Copyright © 2012 John Wiley & Sons, Ltd.     

Opportunistic scheduling for an OFDMA system with multi‐class services

In this paper, we study an opportunistic scheduling problem in an OFDMA system, in which sub‐carriers of the system are allocated to each user in each time slot considering the time‐varying channel condition and QoS requirement of each user. We consider two different classes of services that are represented with different types of utility functions. The utility function for a user in one class is defined as a function of its average data rate, which can be applicable to best‐effort services and the utility function for a user in the other class is defined as a function of its instantaneous data rate, which can be applicable to rate‐sensitive services. Those two types of utility functions have been extensively considered in opportunistic scheduling in wireless networks. However, in most of the previous work, they are considered separately in different problems. In this paper, we formulate a stochastic optimization problem that can treat those two types of utility functions in a single problem, which enables us to implement an opportunistic scheduling algorithm that can consider those two classes of services in a single system in a unified way. Through simulations, we first show that our algorithm provides a good approximation to the optimal solution. In addition, we also verify the appropriateness of our utility models. Copyright © 2010 John Wiley & Sons, Ltd.     

A coordinated multi‐point‐based quality of service provision resource allocation scheme with inter‐cell interference mitigation

The paper investigates resource allocation via power control for inter‐cell interference (ICI) mitigation in an orthogonal frequency division multiple access‐based cellular network. The proposed scheme is featured by a novel subcarrier assignment mechanism at a central controller for ICI, which is further incorporated with an intelligent power control scheme. We formulate the system optimization task into a constrained optimization problem for maximizing accepted users' requirements. To improve the computation efficiency, a fast yet effective heuristic approach is introduced for divide and conquer. Simulation results demonstrate that the proposed resource allocation scheme can significantly improve the network capacity compared with a common approach by frequency reuse. Copyright © 2014 John Wiley & Sons, Ltd.     

QoS‐aware LTE‐A downlink scheduling algorithm: A case study on edge users

4G/LTE‐A (Long‐Term Evolution—Advanced) is the state of the art wireless mobile broadband technology. It allows users to take advantage of high Internet speeds. It makes use of the OFDM technology to offer high speed and provides the system resources both in time and frequency domain. A scheduling algorithm running on the base station holds the allocation of these resources. In this paper, we investigate the performance of existing downlink scheduling algorithms in two ways. First, we look at the performance of the algorithms in terms of throughput and fairness metrics. Second, we suggest a new QoS‐aware fairness criterion, which accepts that the system is fair if it can provide the users with the network traffic speeds that they demand and evaluate the performance of the algorithms according to this metric. We also propose a new QoS‐aware downlink scheduling algorithm (QuAS) according to these two metrics, which increases the QoS‐fairness and overall throughput of the edge users without causing a significant degradation in overall system throughput when compared with other schedulers in the literature.     

Energy‐aware cross‐layer resource allocation in mobile cloud

This paper proposed an energy‐aware cross‐layer mobile cloud resource allocation approach. In this paper, a hybrid cloud architecture is adopted for provisioning mobile service to mobile device users, which include nearby local cloud and remote public cloud. The computation‐intensive tasks can be processed by the remote public cloud, while the delay‐sensitive computation can be processed by the nearby local cloud. On the basis of the system context and mobile user preferences, the energy‐aware cross‐layer mobile cloud resource allocation approach can optimize the consumption of cloud resource and system performance. The cooperation and collaboration among local cloud agent, public cloud supplier, and mobile cloud user are regulated through the economic approach. The energy‐aware cross‐layer mobile cloud resource allocation is performed on the local cloud level and the public cloud level, which comprehensively considers the benefits of all participants. The energy‐aware cross‐layer mobile cloud resource allocation algorithm is proposed, which is evaluated in the experiment environment, and comparison results and analysis are discussed.     

An uplink resource allocation scheme for OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum unoccupied by licensed users. In cognitive radio networks, extra constraints on interference temperature need to be introduced into radio resource allocation. In this paper, the uplink radio resource allocation is investigated for OFDMA‐based cognitive radio networks. In consideration of the characteristics of cognitive radio and OFDMA, an improved water‐filling power allocation scheme is proposed under the interference temperature constraints for optimal performance. Based on the improved water‐filling power allocation, a simple subcarrier allocation algorithm for uplink is proposed. The subcarrier allocation rules are obtained by theoretical deduction. In the uplink subcarrier allocation algorithm, the subcarriers are allocated to the users with the best channel quality initially and then adjusted to improve the system performance. A cursory water‐filling level estimation method is used to decrease the complexity of the algorithm. Asymptotic performance analysis gives a lower bound of the stability of the water‐filling level estimation. The complexity and performance of the proposed radio resource allocation scheme are investigated by theoretical analysis and numerical results. Copyright © 2008 John Wiley & Sons, Ltd.     

Adaptive Resource Allocation for MC‐CDMA and OFDMA in Reconfigurable Radio Systems

This paper studies the uplink resource allocation for multiple radio access (MRA) in reconfigurable radio systems, where multiple‐input and multiple‐output (MIMO) multicarrier‐code division multiple access (MC‐CDMA) and MIMO orthogonal frequency‐division multiple access (OFDMA) networks coexist. By assuming multi‐radio user equipment with network‐guided operation, the optimal resource allocation for MRA is analyzed as a cross‐layer optimization framework with and without fairness consideration to maximize the uplink sum‐rate capacity. Numerical results reveal that parallel MRA, which uses MC‐CDMA and OFDMA networks concurrently, outperforms the performance of each MC‐CDMA and OFDMA network by exploiting the multiuser selection diversity.     

Rate adaptive resource allocation in orthogonal frequency division multiple access system using multi‐objective immune algorithm

Rate adaptive downlink resource allocation in orthogonal frequency division multiple access system is a constraint optimization problem, which is to maximize the minimum data rate of the user subject to constraint that total power cannot exceed a given value. How to handle the constraint is a key issue for constrained optimization problem. Different with the available schemes on constraint handling, the proposed algorithm converts the constraint into an objective. Then, the resource allocation is combined into a multi‐objective optimization problem. An improved multi‐objective optimization algorithm based on artificial immune system is proposed to solve it. The simulation results show that, compared with previous schemes, the proposed algorithm performs remarkable improvement in sum capacity. Copyright © 2013 John Wiley & Sons, Ltd.     

Preference‐based zone selection in 802.16 networks

We examine a new problem called the Zone Selection Problem (ZSP) in wireless Orthogonal Frequency‐Division Multiple Access (OFDMA)‐based systems. We consider the case where the mobile station (MS) informs the base station of its preferences regarding possible working modes supported by the system. In Worldwide Interoperability for Microwave Access (WiMAX) systems, which are used as a practical reference system for constraints and specific modes of operations, each working mode must be assigned at a different time interval called a Zone. Such zone may, in the downlink subframe, define a specific transmission scheme, which can be either single‐input single‐output or one of the multiple‐in multiple‐out (MIMO) modes supported by the system. We define ZSP as a problem where the base station assigns MSs to zones in a way that optimizes the system utilization (in terms of resource usage) while trying to satisfy the preferences of the users as much as possible. This makes ZSP a bi‐objective optimization problem. We derive assignment costs from physical channel models that integrate specific MIMO schemes and channel conditions. We provide an exact solution to ZSP by using a combinatorial optimization abstraction. We propose a simplified and practical mode ranking approach that enables the MS to define its preferences regarding operation in the optional MIMO modes in the system. We prove that ZSP is NP‐hard and describe two heuristic solutions: a greedy approach and a local search approach. Simulation results show the performance of the exact algorithms on a realistic WiMAX system assumptions and present the trade‐off between the user preferences and system preferences. Copyright © 2016 John Wiley & Sons, Ltd.     

Distributed cross‐layer optimization for wireless regional area network‐based cognitive radio networks

This paper presents a study of a cross‐layer design through joint optimization of spectrum allocation and power control for cognitive radio networks (CRNs). The spectrum of interest is divided into independent channels licensed to a set of primary users (PUs). The secondary users are activated only if the transmissions do not cause excessive interference to PUs. In particular, this paper studies the downlink channel assignment and power control in a CRN with the coexistence of PUs and secondary users. The objective was to maximize the total throughput of a CRN. A mathematical model is presented and subsequently formulated as a binary integer programming problem, which belongs to the class of non‐deterministic polynomial‐time hard problems. Subsequently, we develop a distributed algorithm to obtain sub‐optimal results with lower computational complexity. The distributed algorithm iteratively improves the network throughput, which consists of several modules including maximum power calculation, excluded channel sets recording, base station throughput estimation, base station sorting, and channel usage implementation. Through investigating the impacts of the different parameters, simulation results demonstrates that the distributed algorithm can achieve a better performance than two other schemes. Copyright © 2011 John Wiley & Sons, Ltd.     

E‐CLEMA: A cross‐layer design for improved quality of service in mobile WiMAX networks

In this paper, an efficient cross‐layer design that performs joint adaptation of the physical (PHY) and application layers of a mobile WiMAX network is proposed. The design takes into account channel state and performance information from the PHY and medium access control (MAC) layers, respectively. It uses a decision algorithm to evaluate this information, specify unfavorable conditions regarding low channel quality and increased congestion, and take measures by coordinating modulation order, transmission power, and media encoding rate, toward improved overall quality of service (QoS) offered to the user. Extensive simulation results show that the proposed design achieves considerably reduced packet loss and power consumption, combined with increased throughput as compared to a typical mobile WiMAX system. Copyright © 2008 John Wiley & Sons, Ltd.     

A multi‐cell adaptive resource allocation scheme based on potential game for ICIC in LTE‐A

Intercell interference coordination in Third Generation Partnership Project long‐term evolution‐advanced system has received much attention both from the academia and the standardization communities. Moreover, the network architecture of long‐term evolution‐advanced system is modified to take into account coordinated transmission. In this article, we study the dynamic resource allocation problem and potential game theory and propose a multicell adaptive distributed resource allocation algorithm based on potential game. The allocation process is divided into two steps; subchannel is allocated first, and then, transmitted power is optimized dynamically according to a novel pricing factor. Besides, existence and uniqueness of Nash equilibrium of the proposed game model are assured. As a result, intercell interference is well coordinated. Simulation results show that transmitted power is saved efficiently and system fairness is improved to a large extent, accompanied with good performance gain of total and cell‐edge throughputs. Copyright © 2013 John Wiley & Sons, Ltd.     

Graph‐based resource allocation algorithms for multiuser downlink MIMO‐OFDMA networks

Multiuser multiple‐input multiple‐output orthogonal frequency division multiple access (MIMO‐OFDMA) is considered as the practical method to attain the capacity promised by multiple antennas in the downlink direction. However, the joint calculation of precoding/beamforming and resource allocation required by the optimal algorithms is computationally prohibitive. This paper proposes computationally efficient resource allocation algorithms that can be invoked after the precoding and beamforming operations. To support stringent and diverse quality of service requirements, previous works have shown that the resource allocation algorithm must be able to guarantee a specific data rate to each user. The constraint matrix defined by the resource allocation problem with these data rate constraints provides a special structure that lends to efficient solution of the problem. On the basis of the standard graph theory and the Lagrangian relaxation, we develop an optimal resource allocation algorithm that exploits this structure to reduce the required execution time. Moreover, a lower‐complexity suboptimal algorithm is introduced. Extensive simulations are conducted to evaluate the computational and system‐level performance. It is shown that the proposed resource allocation algorithms attain the optimal solution at a much lower computational overhead compared with general‐purpose optimization algorithms used by previous MIMO‐OFDMA resource allocation approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive Resource Allocation for Uplink Carrier Aggregation Scheme in LTE‐A‐Type Networks

Carrier aggregation is an essential feature in the Long Term Evolution‐Advanced (LTE‐A) system, which allows the scalable expansion of the effective bandwidth to be delivered to user equipment (UE) through the concurrent use of radio resources across multiple component carriers (CCs). This system's optimal radio‐resource use has received much attention under simultaneous access (SA) scenarios for multiple CCs (m‐CCs). This letter establishes how many CCs a UE should simultaneously connect to maintain maximum uplink capacity. Under the m‐CC LTE‐A system, the spectral efficiency of the m‐CC SA scheme (m≥2) is compared with that of CC selection (CCS). Numerical results reveal that the 2‐CC SA scheme outperforms CCS and performs almost equally to the m‐CC SA scheme (m≥3).     

基于多维离散粒子群优化的协同 OFDMA 系统跨层资源分配

摘 要：针对多服务情况下协同OFDMA（orthogonal frequency division multiple access）系统的资源分配问题,在基站和中继单独功率约束条件下,以最大化用户的效用(utility)总和为目标,提出了一种基于多维离散粒子群（MDPSO）的渐进最优资源分配算法。该算法采用多值离散变量来编码粒子位置,并针对多维离散空间构建了新的基于概率信息的粒子速度和位置更新算法,且引入变异操作来克服粒子群算法的早熟问题。此外,还采用了迭代注水法进行最优功率分配。仿真结果表明,所提算法在总效用、吞吐量和公平性上均明显优于已有资源分配算法。