认知无线电网络中的资源调度算法研究
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摘要
认知无线电作为一种新兴的无线通信技术,致力于解决当前已被占用的无线频段利用率低的问题。1999年Mitola在软件无线电的基础上提出了认知无线电(Cognitive Radio,CR)的概念。它作为一种基于软件无线电的新的智能无线通信技术,能在时域、频域和空域对较宽的频段进行频谱检测,从而获得授权用户对这些频谱的使用情况,并根据无线环境,对自身参数进行调整。认知无线电技术的主要作用是在不影响授权用户通信的前提下,寻找频谱机会进行非授权用户间的通信。作为一种以非授权的方式动态接入无线频段的先进技术,它有效的提高了频谱利用率。这实现了对无线频谱资源的动态共享,极大的提高了通信系统的频谱利用率。
本文针对基于正交频分多址接入(Orthogonal Frequency DivisionMultiple Access,OFDMA)的系统,从资源调度的角度对不同网络构架下的认知无线电技术进行了研究,目的是优化非授权用户的无线资源分配方案,以最大化非授权与授权系统整体收益,或者是在满足一定的对授权系统干扰限制的前提下,最大化非授权系统收益。论文首先介绍了CR和资源调度的技术背景,随后分别针对集中式(Centralized)CR网络中的最优资源调度方案、分布式(Distributed)CR网络中频谱分配的最优性(Optimality).分布式CR网络中功率优化算法的收敛性(Convergence).分布式CR网络中的次优资源调度算法设计、以及结合路由选择的多跳分布式CR网络中的跨层设计方案等几方面进行研究。本文的主要贡献如下：
第一,针对集中式CR网络中的资源调度方案,提出了一种基于一般收益函数形式的最优资源调度方案。目前,对于OFDMA系统的子载波和功率分配方案已有大量研究,但在CR网络中,为了保护授权用户,非授权用户的资源调度受到一定的限制。这里我们限制所有非授权用户在任一授权接收机处所产生的累加干扰,使其必须低于一个预定义的门限。之前的研究由于没有考虑该限制条件,已有的最大化多址信道(Multiple Access Channel,MAC)吞吐量的多用户子载波和功率分配方法变得不再适用。本文基于最优化理论,针对该问题建立相应的凸优化模型。通过使用对偶分解方法,推导出最优的子载波和功率分配方案,并基于此结论提出实际算法。该算法应用了拉格朗日对偶方法,通过迭代得到最优的拉格朗日(Lagrangian)乘子。最后,给出了仿真结果和相应分析。
第二,对于分布式CR网络,其网络架构可以抽象为高斯干扰信道(Gaussian Interference Channel, GIC)模型。GIC模型的信道容量和GIC系统中分布式功率优化算法的收敛性仍是目前理论研究的热点,而这二者也是分布式CR网络中资源调度算法设计的理论基础,本文在这两方面的创新点包括：
针对信道容量的问题,论文以GIC信道为模型,研究比较了Overlay和Underlay的频谱共享方式,即频分复用(Frequency Division Multiplexing, FDM)与频谱重用(Frequency Reusing)的频谱共享方式,对系统吞吐量的影响。以最大化系统总吞吐量为目标,推导得到了应选择FDM方式进行非授权和授权用户间的频谱共享的充分条件。另外,针对收敛性的问题,论文研究了在一般的收益函数形式下,非协作分布式功率优化的收敛性要求。对于该问题,已有的研究均局限于香农(Shannon)信道容量形式的收益函数,本文将其拓展到一般形式的收益函数,推导得到了保证算法收敛的充分条件。
第三,基于上述分布式CR网络资源调度的理论研究,针对实际网络应用场景进行了算法设计。具体来说,网络场景为分布式CR网络,重用蜂窝上行资源进行数据传输,以提高网络整体频谱效率。为了实现CR网络和蜂窝网络间有效的资源共享,我们提出了一种干扰协调方案。在该方案中,考虑到多数现有蜂窝网络的快速调度特性,CR终端使用一种基于蜂窝用户调度信息的功控方案,以适应蜂窝通信所导致的时变干扰环境。此外,为了减少由信道快衰落所造成的信道不确定性,我们采用了随机优化方法以跟踪长期信道状态。结合对该问题的凸分析,设计了实际应用算法,可融入到现有的蜂窝网络协议之中。最后,在均方误差的意义下分析证明了该算法的收敛性,同时,仿真结果对算法在链路和系统方面的性能进行了研究。
第四,在基于多跳的分布式CR网络中,结合路由选择问题考虑了分布式CR网络的跨层设计问题。论文以最大化不同类型的端到端(Peer to Peer, P2P)性能为优化目标,旨在解决路由选择和资源调度的联合优化问题。论文以冲突图的方式建模CR链路之间的干扰关系,首先证明该优化问题可以建模为一个凸优化问题,并推导得到了其最优解表达式。基于这一结论,我们提出了一个适用于分布式实现的算法,算法中应用拉格朗日对偶理论和弗兰克-沃尔夫(Frank-Wolfe)方法迭代得到最优解。最后,仿真结论揭示了端到端瓶颈吞吐量、跳数和干扰门限之间的关系。
As a promising wireless communications technology, cognitive radio aims to solve the under-utilization problem of the occupied radio spectrum currently. In 1999, based on software defined radio (SDR), Mitola proposed the concept of cognitive radio (CR). As a new intelligent SDR-based wireless communication technology, it enables spectrum sensing in the time, frequency and spatial domain on a wide-band spectrum, to obtain the activity of authorized users on the licensed spectrum, and adjust their own parameters according to the wireless environment. The main effect of cognitive radio technology is to find the spectrum opportunities for communication between unlicensed users, without interfering the communication between licensed users. As an advanced technology accessing to the wireless spectrum dynamically in an unlicensed manner, cognitive radio improves the spectrum efficiency effectively, enables the dynamic wireless spectrum sharing, and greatly improves the spectrum utilization of communication systems.
For orthogonal frequency division multiple access (OFDMA) based systems, from the perspective of resource scheduling, this paper studies cognitive radio technology for different network architectures. It aims to optimize the wireless resource allocation of unlicensed users to maximize the sum utility of licensed and unlicensed systems, or to maximize the utility of unlicensed system under specific interference constraint to protect the licensed system. This paper introduces the technical background of cognitive radio and resource scheduling first, and then describes the research work on optimal resource scheduling schemes in centralized CR network, optimality of resource scheduling schemes and convergence of power optimization algorithm in distributed CR network, sub-optimal resource scheduling algorithm design in distributed CR network, cross-layer design considering route selection in a multi-hop CR network. Main contributions of this paper are as follows:
Firstly, for resource scheduling in centralized CR network, an optimal resource scheduling scheme is proposed based on a general form of utility function. There exists a lot of study on subcarrier and power allocation scheme in OFDMA system, but in CR networks, in order to protect the licensed users, resource scheduling for unlicensed users is subject to some constraints. In this paper, the sum of interference caused by all unlicensed users at each licensed receiver must be below a predefined threshold. Since the existing study did not consider this constraint, the existing subcarrier and power allocation schemes for throughput maximization of multi-access channel (MAC) are no longer applicable. Based on the optimization theory, this paper models the problem as a convex optimization program. Using the dual decomposition method, the optimal subcarrier and power allocation scheme is derived. Based on it, the practical algorithm is proposed, which applies the Lagrangian dual method to obtain the optimal Lagrangian multipliers iteratively. Finally, the simulation result is presented with corresponding analysis.
Secondly, for distributed CR network, the network architecture can be modeled as a Gaussian interference channel (GIC) model. The channel capacity of GIC and convergence of distributed power optimization algorithm are still research hot points, and they are also the theoretical basis of resource scheduling design in distributed CR network. In this paper, the innovative points on the two aspects include:
For the channel capacity problem, under the model of GIC, the paper studies and compares the impact on system throughput of two different spectrum sharing approaches, i.e., the Overlay manner and the Underlay manner, namely, frequency division multiplexing (FDM) and spectrum reusing. In the objective of maximizing total system throughput, the sufficient condition is derived to choose FDM rather than Frequency Reusing for spectrum sharing between licensed and unlicensed users. Besides, for the convergence problem, under a general form of utility function, this paper studies the convergence of non-cooperative distributed power optimization scheme. For this problem, the existing research is limited to the Shannon capacity utility function. This article extends it to the general form of utility function, and derives the sufficient conditions to guarantee the algorithm convergence.
Thirdly, based on the theoretical work for distributed CR network above, algorithm design is considered for practical network scenario. Specifically, the network scenario is the distributed CR network, which reuses the cellular uplink resources for data transmission, to improve the spectrum efficiency of the whole network. We propose an interference coordination scheme to achieve efficient resource sharing between the CR sub-system and cellular sub-system. In the proposed scheme, taking into account of the fast dynamic scheduling feature of most existing cellular network, CR links employ a cellular UE scheduling based transmission power control mechanism, to adapt to the time-varying interference environment caused by cellular communication. In addition, in order to reduce the channel uncertainty caused by the fast fading, we use the stochastic optimization method to track the long-term channel state. Finally, based on convex analysis to the optimization problem, a practical scheme is developed, which can be integrated into the existing cellular network protocols. At last, the convergence is proved in a mean-square-error sense, and the link and system performance of the interference coordination scheme are investigated by simulation results.
Fourth, in the multi-hop distributed CR networks, combining with route selection, the cross-layer design problem is considered. In the objective of maximizing different types of Peer-to-Peer (P2P) performance, this paper aims to solve the joint optimization problem of route selection and resource scheduling. Firstly, modeling the interference relationship between the links in a way of conflict graph, it is proved that the optimization problem can be modeled as a convex optimization problem, and the expression of the optimal solution is derived. Based on this conclusion, we propose an iterative algorithm for distributed implementation, which applies Lagrange duality theory and Frank-Wolf method to achieve the optimal solution. The simulation results study the relationship between P2P bottleneck throughput, hops and interference threshold.
本文针对基于正交频分多址接入(Orthogonal Frequency DivisionMultiple Access,OFDMA)的系统,从资源调度的角度对不同网络构架下的认知无线电技术进行了研究,目的是优化非授权用户的无线资源分配方案,以最大化非授权与授权系统整体收益,或者是在满足一定的对授权系统干扰限制的前提下,最大化非授权系统收益。论文首先介绍了CR和资源调度的技术背景,随后分别针对集中式(Centralized)CR网络中的最优资源调度方案、分布式(Distributed)CR网络中频谱分配的最优性(Optimality).分布式CR网络中功率优化算法的收敛性(Convergence).分布式CR网络中的次优资源调度算法设计、以及结合路由选择的多跳分布式CR网络中的跨层设计方案等几方面进行研究。本文的主要贡献如下：
第一,针对集中式CR网络中的资源调度方案,提出了一种基于一般收益函数形式的最优资源调度方案。目前,对于OFDMA系统的子载波和功率分配方案已有大量研究,但在CR网络中,为了保护授权用户,非授权用户的资源调度受到一定的限制。这里我们限制所有非授权用户在任一授权接收机处所产生的累加干扰,使其必须低于一个预定义的门限。之前的研究由于没有考虑该限制条件,已有的最大化多址信道(Multiple Access Channel,MAC)吞吐量的多用户子载波和功率分配方法变得不再适用。本文基于最优化理论,针对该问题建立相应的凸优化模型。通过使用对偶分解方法,推导出最优的子载波和功率分配方案,并基于此结论提出实际算法。该算法应用了拉格朗日对偶方法,通过迭代得到最优的拉格朗日(Lagrangian)乘子。最后,给出了仿真结果和相应分析。
第二,对于分布式CR网络,其网络架构可以抽象为高斯干扰信道(Gaussian Interference Channel, GIC)模型。GIC模型的信道容量和GIC系统中分布式功率优化算法的收敛性仍是目前理论研究的热点,而这二者也是分布式CR网络中资源调度算法设计的理论基础,本文在这两方面的创新点包括：
针对信道容量的问题,论文以GIC信道为模型,研究比较了Overlay和Underlay的频谱共享方式,即频分复用(Frequency Division Multiplexing, FDM)与频谱重用(Frequency Reusing)的频谱共享方式,对系统吞吐量的影响。以最大化系统总吞吐量为目标,推导得到了应选择FDM方式进行非授权和授权用户间的频谱共享的充分条件。另外,针对收敛性的问题,论文研究了在一般的收益函数形式下,非协作分布式功率优化的收敛性要求。对于该问题,已有的研究均局限于香农(Shannon)信道容量形式的收益函数,本文将其拓展到一般形式的收益函数,推导得到了保证算法收敛的充分条件。
第三,基于上述分布式CR网络资源调度的理论研究,针对实际网络应用场景进行了算法设计。具体来说,网络场景为分布式CR网络,重用蜂窝上行资源进行数据传输,以提高网络整体频谱效率。为了实现CR网络和蜂窝网络间有效的资源共享,我们提出了一种干扰协调方案。在该方案中,考虑到多数现有蜂窝网络的快速调度特性,CR终端使用一种基于蜂窝用户调度信息的功控方案,以适应蜂窝通信所导致的时变干扰环境。此外,为了减少由信道快衰落所造成的信道不确定性,我们采用了随机优化方法以跟踪长期信道状态。结合对该问题的凸分析,设计了实际应用算法,可融入到现有的蜂窝网络协议之中。最后,在均方误差的意义下分析证明了该算法的收敛性,同时,仿真结果对算法在链路和系统方面的性能进行了研究。
第四,在基于多跳的分布式CR网络中,结合路由选择问题考虑了分布式CR网络的跨层设计问题。论文以最大化不同类型的端到端(Peer to Peer, P2P)性能为优化目标,旨在解决路由选择和资源调度的联合优化问题。论文以冲突图的方式建模CR链路之间的干扰关系,首先证明该优化问题可以建模为一个凸优化问题,并推导得到了其最优解表达式。基于这一结论,我们提出了一个适用于分布式实现的算法,算法中应用拉格朗日对偶理论和弗兰克-沃尔夫(Frank-Wolfe)方法迭代得到最优解。最后,仿真结论揭示了端到端瓶颈吞吐量、跳数和干扰门限之间的关系。
As a promising wireless communications technology, cognitive radio aims to solve the under-utilization problem of the occupied radio spectrum currently. In 1999, based on software defined radio (SDR), Mitola proposed the concept of cognitive radio (CR). As a new intelligent SDR-based wireless communication technology, it enables spectrum sensing in the time, frequency and spatial domain on a wide-band spectrum, to obtain the activity of authorized users on the licensed spectrum, and adjust their own parameters according to the wireless environment. The main effect of cognitive radio technology is to find the spectrum opportunities for communication between unlicensed users, without interfering the communication between licensed users. As an advanced technology accessing to the wireless spectrum dynamically in an unlicensed manner, cognitive radio improves the spectrum efficiency effectively, enables the dynamic wireless spectrum sharing, and greatly improves the spectrum utilization of communication systems.
For orthogonal frequency division multiple access (OFDMA) based systems, from the perspective of resource scheduling, this paper studies cognitive radio technology for different network architectures. It aims to optimize the wireless resource allocation of unlicensed users to maximize the sum utility of licensed and unlicensed systems, or to maximize the utility of unlicensed system under specific interference constraint to protect the licensed system. This paper introduces the technical background of cognitive radio and resource scheduling first, and then describes the research work on optimal resource scheduling schemes in centralized CR network, optimality of resource scheduling schemes and convergence of power optimization algorithm in distributed CR network, sub-optimal resource scheduling algorithm design in distributed CR network, cross-layer design considering route selection in a multi-hop CR network. Main contributions of this paper are as follows:
Firstly, for resource scheduling in centralized CR network, an optimal resource scheduling scheme is proposed based on a general form of utility function. There exists a lot of study on subcarrier and power allocation scheme in OFDMA system, but in CR networks, in order to protect the licensed users, resource scheduling for unlicensed users is subject to some constraints. In this paper, the sum of interference caused by all unlicensed users at each licensed receiver must be below a predefined threshold. Since the existing study did not consider this constraint, the existing subcarrier and power allocation schemes for throughput maximization of multi-access channel (MAC) are no longer applicable. Based on the optimization theory, this paper models the problem as a convex optimization program. Using the dual decomposition method, the optimal subcarrier and power allocation scheme is derived. Based on it, the practical algorithm is proposed, which applies the Lagrangian dual method to obtain the optimal Lagrangian multipliers iteratively. Finally, the simulation result is presented with corresponding analysis.
Secondly, for distributed CR network, the network architecture can be modeled as a Gaussian interference channel (GIC) model. The channel capacity of GIC and convergence of distributed power optimization algorithm are still research hot points, and they are also the theoretical basis of resource scheduling design in distributed CR network. In this paper, the innovative points on the two aspects include:
For the channel capacity problem, under the model of GIC, the paper studies and compares the impact on system throughput of two different spectrum sharing approaches, i.e., the Overlay manner and the Underlay manner, namely, frequency division multiplexing (FDM) and spectrum reusing. In the objective of maximizing total system throughput, the sufficient condition is derived to choose FDM rather than Frequency Reusing for spectrum sharing between licensed and unlicensed users. Besides, for the convergence problem, under a general form of utility function, this paper studies the convergence of non-cooperative distributed power optimization scheme. For this problem, the existing research is limited to the Shannon capacity utility function. This article extends it to the general form of utility function, and derives the sufficient conditions to guarantee the algorithm convergence.
Thirdly, based on the theoretical work for distributed CR network above, algorithm design is considered for practical network scenario. Specifically, the network scenario is the distributed CR network, which reuses the cellular uplink resources for data transmission, to improve the spectrum efficiency of the whole network. We propose an interference coordination scheme to achieve efficient resource sharing between the CR sub-system and cellular sub-system. In the proposed scheme, taking into account of the fast dynamic scheduling feature of most existing cellular network, CR links employ a cellular UE scheduling based transmission power control mechanism, to adapt to the time-varying interference environment caused by cellular communication. In addition, in order to reduce the channel uncertainty caused by the fast fading, we use the stochastic optimization method to track the long-term channel state. Finally, based on convex analysis to the optimization problem, a practical scheme is developed, which can be integrated into the existing cellular network protocols. At last, the convergence is proved in a mean-square-error sense, and the link and system performance of the interference coordination scheme are investigated by simulation results.
Fourth, in the multi-hop distributed CR networks, combining with route selection, the cross-layer design problem is considered. In the objective of maximizing different types of Peer-to-Peer (P2P) performance, this paper aims to solve the joint optimization problem of route selection and resource scheduling. Firstly, modeling the interference relationship between the links in a way of conflict graph, it is proved that the optimization problem can be modeled as a convex optimization problem, and the expression of the optimal solution is derived. Based on this conclusion, we propose an iterative algorithm for distributed implementation, which applies Lagrange duality theory and Frank-Wolf method to achieve the optimal solution. The simulation results study the relationship between P2P bottleneck throughput, hops and interference threshold.
引文
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