An enhanced MAC protocol based on the IEEE 802.11 for data relay satellite systems

Data relay satellite (DRS) systems play an important role in space information networks. Characterized by highly dynamic topology and discontinuous communication links, it is suggested that the IEEE 802.11 protocol employed in such a network could be more flexible. However, such a terrestrial network protocol could not be applied to DRS systems directly, nor supports a fast response due to the long propagation delay and severe packet collision. To address this challenge, we proposed an enhanced media access control (MAC) protocol based on the IEEE 802.11 protocol providing multiaccess for low earth orbit (LEO) distributed constellations. In this paper, we investigated the access delay performance of the proposed protocol in our model. Then, we derived a contention window adaption by using an iteration algorithm that can dynamically adjust the values of the contention window depending on the number of user satellites in the communication coverage. Simulation results show that the average access delay does not exceed 20 seconds, which is significantly lower than the standard protocol. Moreover, the traffic threshold is increased to 0.6, and the maximum throughput has doubled compared with the standard protocol. It is proved that the enhanced MAC protocol shows a better performance in DRS systems.     

基于能量效率的分布式星群下行链路功率分配方法研究

针对多波束卫星通信系统星上资源稀缺和能量利用效率不高的问题,本文提出了分布式星群网络下行链路中兼顾系统功耗和数据速率的功率分配方法,通过合理的资源分配来优化系统的能量效率.首先建立分布式星群功率分配模型,将复杂的分式问题转化为易于求解的减法形式问题,然后基于凸优化理论,提出功耗-数据速率权衡功率分配算法,并讨论了能量效率（energy efficiency）与频谱效率（spectral efficiency）之间的权衡关系.仿真结果验证了提出算法的有效性和EE-SE权衡关系,并分析了电路功耗对系统性能的影响.     

An online power allocation algorithm based on deep reinforcement learning in multibeam satellite systems

Dynamic power allocation (DPA) is the key technique to improve the system throughput by matching the offered capacity with that required among distributed beams in multibeam satellite systems. Existing power allocation studies tend to adopt the metaheuristic optimization algorithms such as the genetic algorithm. The achieved DPA cannot adapt to the dynamic environments due to the varying traffic demands and the channel conditions. To solve this problem, an online algorithm named deep reinforcement learning‐based dynamic power allocation (DRL‐DPA) algorithm is proposed in this paper. The key idea of the proposed DRL‐DPA lies in the online power allocation decision making other than the offline way of the traditional metaheuristic methods. Simulation results show that the proposed DRL‐DPA algorithm can improve the system performance in terms of system throughput and power consumption in multibeam satellite systems.     

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。     

A Dynamic Bandwidth Allocation Scheme for a Multi‐spot‐beam Satellite System

A multi‐spot‐beam satellite is an attractive technique for future satellite communications since it can support high data rates by projecting high power density to each spot beam and can reuse a frequency in different cells to increase the total system capacity. In this letter, we propose a resource management technique adjusting the bandwidth of each beam to minimize the difference between the traffic demand and allocated capacity. This represents a reasonable solution for dynamic bandwidth allocation, considering a trade‐off between the maximum total capacity and fairness among the spot beams with different traffic demands.     

Distributed two‐hop proportional fair resource allocation in Long Term Evolution Advanced networks

In Long Term Evolution Advanced networks with Type I in‐band half‐duplex decode‐and‐forward relay nodes, proportional fair (PF) resource allocation is aiming at guaranteeing two‐hop match and optimising global proportional fairness. The two‐hop match is defined as equal data rates in the access links and the corresponding backhaul links. The global proportional fairness is between all the user equipments served by the evolved nodes B and the relay nodes. Existing centralised schemes achieve these targets at the cost of enormous channel state information (CSI) exchange. Existing distributed schemes focus on resource partitioning and employ a traditional single‐hop PF scheduling algorithm in access links, with less CSI exchange. The traditional PF scheduling algorithm maximises single‐hop proportional fairness between the data rates in the access links rather than two‐hop proportional fairness between the end‐to‐end data rates in the two hops. In order to reduce CSI exchange and at the same time to maximise the two‐hop proportional fairness, a distributed two‐hop PF resource allocation scheme is proposed. The proposed scheme includes two‐hop PF resource scheduling algorithms and adaptive resource partitioning algorithms, applied in different two‐hop transmission protocols. Simulation results demonstrate the proposed scheme is better than the existing distributed schemes in obtaining better proportional fairness and larger cell‐edge user equipment throughputs. Copyright © 2014 John Wiley & Sons, Ltd.     

无线多址接入网络编码中继的信道分配算法

无线多址接入中继网络中,用户可选择是否接入中继,同时中继也可选择所服务的用户。在中继处应用网络编码技术可使单个中继同时服务于2个用户共享同一时频资源进行无干扰信息传输。基站采用联合检测方法恢复原始信息,从而得到传输速率的提升。针对多用户多中继场景,为了进一步提升系统的吞吐量,需要为用户选择合适的中继协助其传输,考虑到多址网络编码中继的中继选择问题是一个复杂的优化问题,为了降低其求解复杂度,分别采用基于贪婪准则和考虑用户公平性的信道分配算法进行求解。仿真结果表明,所提信道分配算法相比于随机信道分配可获得较大的性能增益,并且基于贪婪准则的算法性能优于考虑用户公平性的算法。     

Satellite constellation of MEO and IGSO network routing with dynamic grouping

Because inter‐satellite links (ISLs) among the distributed satellite nodes can be used to support autonomous control in satellite system operation to reduce dependency on the ground stations, it becomes a popular communication paradigm for the future satellite systems. However, this introduces great technical challenges, particularly for routing protocol to support such space communication system. Facing the challenges, we present out study of routing technology in this paper tailored for satellite network of MEO (Table 1) and IGSO with ISLs in addition to satellite–ground links. The study aims to explore the routing strategies and algorithms of satellite network based on the evolution law of network topology to provide reference design for data exchange in autonomous satellite system. A comprehensive investigation, ranging from the analysis of relevant factors affecting data exchange in satellite networks to the primary application and resource constraints in designing satellite routing strategy, has been conducted. Our main contribution is to propose an on‐demand computing and caching centralized routing strategy and algorithm on the satellite network. The routing strategy and algorithm is designed for satellite network topology dynamic grouping. The route calculation for user data transmission is divided into three phases: direction estimation, direction enhancement, and congestion avoidance. The strategy and algorithm provide significant advantages of high efficiency, low complexity, and flexible configuration, by which the satellite networks can provide the features of flexible configure, efficient transferring, easy management, structural survivability, and great potential in scalability. Copyright © 2013 John Wiley & Sons, Ltd.     

虚拟两天线蜂窝网络中考虑中继公平性的协作博弈调度方法(英文)

In thsssse cellular network, Relay Stations (RSs) help to improve the system performance; however, little work has been done considering the fairness of RSs. In this paper, we study the cooperative game approaches for scheduling in the wireless relay networks with two-virtual-antenna array mode. After defining the metric of relay channel capacity, we form a cooperative game for scheduling and present the interpretation of three different utilization objectives physically and mathematically. Then, a Nash Bargaining Solution (NBS) is utilized for resource allocation considering the traffic load fairness for relays. After proving the existence and uniqueness of NBS in Cooperative Game (CG-NBS), we are able to resolve the resource allocation problem in the cellular relay network by the relay selection and subcarrier assignment policy and the power allocation algorithm for both RSs and UEs. Simulation results reveal that the proposed CG-NBS scheme achieves better tradeoff between relay fairness and system throughput than the conventional Maximal Rate Optimization and Maximal Minimal Fairness methods.     

一种新的GEO/LEO双层星座路由算法

针对多层卫星星座网络的复杂通信环境和特殊应用背景,提出一种新的基于优先级的星上分布式路由算法( PDRA)。 PDRA算法采用新的分层管理策略,根据信息重要程度设置优先级,在拓扑快照起始时刻进行路由计算与更新,信息传输过程中采用拥塞回避策略。理论分析和仿真验证表明,PDRA算法与现有典型卫星星座网络路由算法相比性能优越,能够很好地利用GEO/LEO双层星座特点,有较低的数据丢包率和较高的吞吐量,可有效避免链路拥塞,并能保证重要信息实时可靠传输。     

Tasking planning based on task splitting and merging in relay satellite network

To handle the low planning efficiency of the tasks with too long or too short service time,a task planning scheme was proposed based on task splitting and merging for relay satellite systems.First,a task splitting and merging was developed to transfer the task requirements of user to task units which could be planned with high efficiency.Secondly,based on the parallel machine scheduling model,the optimization problem of the task unit planning to maximize the number of completed tasks in the network was built.Further,a heuristic polynomial time scheduling algorithm was proposed.Simulation results show that compared to the traditional scheme,the task planning scheme perform better in terms of completed task number,resource utilization and fairness.     

Stability and sensitivity for congestion control in wireless mesh networks with time varying link capacities

A critical challenge for wireless mesh networks is the design of efficient transport protocols that provide high bandwidth utilization and desired fairness in the multi-hop, wireless environment. While extensive efforts have been devoted to providing optimization based, distributed congestion control schemes for efficient bandwidth utilization and fair allocation in both wireline and wireless networks, a common assumption therein is fixed link capacities. This unfortunately will limit the application scope in wireless mesh networks where channels are ever changing. In this paper, we explicitly model link capacities to be time varying and investigate congestion control problems in multi-hop wireless networks. In particular we propose a primal–dual congestion control algorithm which is proved to be trajectory stable in the absence of feedback delay. Different from system stability around a single equilibrium point, trajectory stability guarantees the system is stable around a time varying reference trajectory. Moreover, we obtain sufficient conditions for the scheme to be locally stable in the presence of delay. Our key technique is to model time variations of capacities as perturbations to a constant link. Furthermore, to study the robustness of the algorithm against capacity variations, we investigate the sensitivity of the control scheme and through simulations to study the tradeoff between stability and sensitivity.     

基于分层和模拟退火算法的动态信道分配方案

This paper proposes a dynamic channel allocation scheme based on cognitive radio （CR）. Firstly, the channel probing based on MMSE criterion is implemented, with which the probability distribution of channels in use by the primary user is given. Next, take the distances between the CR users and the primary user as basis to stratify the CR users, among the layers; the simulated annealing （SA） algorithm is used to implement the channel assigmnent. This algorithm differs from the well-known 0-1 matrix based allocation scheme, and keeps a good tradeoff between complexity, capacity as well as the fairness problems. The simulation results show that this algorithm can improve the allocation efficiency effectively.     

Resource allocation with proportional rate fairness in orthogonal frequency division multiple access relay networks

We address the problem of subchannel and transmission power allocation in orthogonal frequency division multiple access relay networks with an aim to maximize the sum rate and maintain proportional rate fairness among users. Because the formulated problem is a mixed‐integer nonlinear optimization problem with an extremely high computational complexity, we propose a low‐complexity suboptimal algorithm, which is a two‐step separated subchannel and power allocation algorithm. In the first step, subchannels are allocated to each user, whereas in the second step, the optimal power allocation is carried out on the basis of the given subchannel allocation and the nonlinear interval Gauss–Seidel method. Simulation results have demonstrated that the proposed algorithm can achieve a good trade‐off between the efficiency and the fairness compared with two other existing relevant algorithms. In particular, the proposed algorithm can always achieve 100% fairness under various conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

自适应遗传算法的数据中继卫星光网络资源调度算法

以数据中继卫星光网络系统资源、任务和约束条件为参量,以任务对资源的选择为优化对象,提出了一种基于自适应遗传算法的数据中继卫星光网络资源调度算法.综合考虑多中继星、多时间窗口、多光学天线以及任务优先级要求,建立调度模型;采用当前任务调度时间的确定和后续任务可见时间窗口的更新的调度操作,对不同资源的任务集合进行调度安排并实现了可见时间窗口的动态更新,获得调度任务的总权值并将其作为参量计算适应度值,最后通过改进的自适应遗传算法对不同调度方案进行寻优.以3颗中继星、12颗用户星,6个光天线,60个任务为条件设置了仿真场景,仿真结果表明该算法在收敛速度、调度效率方面具有优势,适应于多任务、多天线的数据中继卫星光网络系统资源调度.     

Next‐generation global satellite system with mega‐constellations

Mega satellite constellations in low earth orbit (LEO) will provide complete global coverage; rapidly enhance overall capacity, even for unserved areas; and improve the quality of service (QoS) possible with lower signal propagation delays. Complemented by medium earth orbit (MEO) and geostationary earth orbit (GEO) satellites and terrestrial network components under a hybrid communications architecture, these constellations will enable universal 5G service across the world while supporting diverse 5G use cases. With an unobstructed line‐of‐sight visibility of approximately 3 min, a typical LEO satellite requires efficient user terminal (UT), satellite, gateway, and intersatellite link handovers. A comprehensive mobility design for mega‐constellations involves cost‐effective space and ground phased‐array antennas for responsive and seamless tracking. An end‐to‐end multilayer protocol architecture spanning space and terrestrial technologies can be used to analyze and ensure QoS and mobility. A scalable routing and traffic engineering design based on software‐defined networking adequately handles continuous variability in network topology, differentiated user demands, and traffic transport in both temporal and spatial dimensions. The space‐based networks involving mega‐constellations will be better integrated with their terrestrial counterparts by fully leveraging the multilayer 5G framework, which is the foundational feature of our hybrid architecture.     

Real-time resource allocation for LEO satellite constellations

The paper addresses the need of controling the access of terminals with guaranteed ressources on the high dynamic systems offered by LEO satellite constellations. A call-access-control scheme that guarantees the reservation of permanent resources of satellite constellations in $O(\sqrt(n)\hbox{log}(n))The paper addresses the need of controling the access of terminals with guaranteed ressources on the high dynamic systems offered by LEO satellite constellations. A call-access-control scheme that guarantees the reservation of permanent resources of satellite constellations in time, where n is the number of user present in the system, is described. A tradeoff between computational time of call-access-control and optimization of the use of the spectrum is identified. Some experimental results are presented.

Jér?me GaltierEmail:

     

Resource allocation in satellite networks: certainty equivalent approaches versus sensitivity estimation algorithms

In this paper, we consider a resource allocation problem for a satellite network, where variations of fading conditions are added to those of traffic load. Since the capacity of the system is finite and divided in finite discrete portions, the resource allocation problem reveals to be a discrete stochastic programming one, which is typically NP‐hard. We propose a new approach based on the minimization over a discrete constraint set using an estimation of the gradient, obtained through a ‘relaxed continuous extension’ of the performance measure. The computation of the gradient estimation is based on the infinitesimal perturbation analysis technique, applied on a stochastic fluid model of the network. No closed‐forms of the performance measure, nor additional feedback concerning the state of the system, and very mild assumptions on the probabilistic properties about the statistical processes involved in the problem are requested. Such optimization approach is compared with a dynamic programming algorithm that maintains a perfect knowledge about the state of the satellite network (traffic load statistics and fading levels). The comparison shows that the sensitivity estimation capability of the proposed algorithm allows to maintain the optimal resource allocation in dynamic conditions and it is able to provide even better performance than the one reached by employing the dynamic programming approach. Copyright © 2004 John Wiley & Sons, Ltd.     

Resource allocation for multiuser cognitive OFDM networks with proportional rate constraints

In this paper we study the resource allocation problem for the multiuser orthogonal frequency division multiplexing (OFDM)‐based cognitive radio (CR) systems with proportional rate constraints. The mutual interference introduced by primary user (PU) and cognitive radio user (also referred to secondary user, SU) makes the optimization problem of CR systems more complex. Moreover, the interference introduced to PUs must be kept under a given threshold. In this paper, the highest achievable rate of each OFDM subchannel is calculated by jointly considering the channel gain and interference level. First, a subchannel is assigned to the SU with the highest achievable rate. The remaining subchannels are always allocated to the SU that suffers the severest unjustness. Second, an efficient bit allocation algorithm is developed to maximize the sum capacity, which is again based on the highest achievable rate of each subchannel. Finally, an adjustment procedure is designed to maintain proportional fairness. Simulation results show that the proposed algorithm maximizes the sum capacity while keeping the proportional rate constraints satisfied. The algorithm exhibits a good tradeoff between sum capacity maximization and proportional fairness. Furthermore, the proposed algorithm has lower complexity compared with other algorithms, rendering it promising for practical applications. Copyright © 2011 John Wiley & Sons, Ltd.     

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.