This paper considers the resource allocation problem in an Orthogonal Frequency Division Multiple Access (OFDMA) based cognitive radio (CR) network, where the CR base station adopts full overlay scheme to transmit both private and open information to multiple users with average delay and power constraints. A stochastic optimization problem is formulated to develop flow control and radio resource allocation in order to maximize the long-term system throughput of open and private information in CR system and ensure the stability of primary system. The corresponding optimal condition for employing full overlay is derived in the context of concurrent transmission of open and private information. An online resource allocation scheme is designed to adapt the transmission of open and private information based on monitoring the status of primary system as well as the channel and queue states in the CR network. The scheme is proven to be asymptotically optimal in solving the stochastic optimization problem without knowing any statistical information. Simulations are provided to verify the analytical results and efficiency of the scheme.
Besides the interference constraints, the works of delay aware transmission are also quite relative to this paper. Huang and Fang in @cite_7 investigate both reliability and delay constraints in routing design for wireless sensor network. in @cite_9 summarize three approaches to deal with delay-aware resource allocation in wireless networks. A constrained predictive control strategy is proposed in @cite_27 to compensate for network-induced delays with stability guarantee. Those three methods are based on large deviation theory, Markov decision theory and Lyapunov optimization techniques. As to the first two methods, they have to know some statistical information on channel state and random arrival data rate to design algorithm, while these prior knowledge is expensive to get, even unavailable. To overcome this problem, many authors pay attention to Lyapunov optimization techniques. References @cite_40 and @cite_16 investigate scheduling in multi-hop wireless networks and resource allocation in cooperative communications, respectively as two typical applications of Lyapunov optimization in delay-limited system. In this paper, we utilize this tool to dispose the resource allocation problem in OFDMA-based CR networks.
@cite_7 @cite_9 @cite_27 @cite_40 @cite_16
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Sensor nodes are densely deployed to accomplish various applications because of the inexpensive cost and small size. Depending on different applications, the traffic in the wireless sensor networks may be mixed with time-sensitive packets and reliability-demanding packets. Therefore, QoS routing is an important issue in wireless sensor networks. Our goal is to provide soft-QoS to different packets as path information is not readily available in wireless networks. In this paper, we utilize the multiple paths between the source and sink pairs for QoS provisioning. Unlike E2E QoS schemes, soft-QoS mapped into links on a path is provided based on local link state information. By the estimation and approximation of path quality, traditional NP-complete QoS problem can be transformed to a modest problem. The idea is to formulate the optimization problem as a probabilistic programming, then based on some approximation technique, we convert it into a deterministic linear programming, which is much easier and convenient to solve. More importantly, the resulting solution is also one to the original probabilistic programming. Simulation results demonstrate the effectiveness of our approach. In this paper, a comprehensive survey is given on several major systematic approaches in dealing with delay-aware control problems, namely the equivalentrate constraint approach, the Lyapunov stability drift approach, and the approximate Markov decision process approach using stochastic learning. These approaches essentially embrace most of the existing literature regarding delay-aware resource control in wireless systems. They have their relative pros and cons in terms of performance, complexity, and implementation issues. For each of the approaches, the problem setup, the general solution, and the design methodology are discussed. Applications of these approaches to delay-aware resource allocation are illustrated with examples in single-hop wireless networks. Furthermore, recent results regarding delay-aware multihop routing designs in general multihop networks are elaborated. Finally, the delay performances of various approaches are compared through simulations using an example of the uplink OFDMA systems. This paper investigates the problem of stabilizing predictive control for networked control systems with state and input constraints. Both sensor-to-controller and controller-to-actuator delays are considered and described by a multirate method. The control scheme is characterized as a constrained finite horizon predictive control optimization problem with a multirate network-induced delays compensation strategy. It is shown that the proposed predictive controller not only efficiently reduces the negative effects of the network-induced delays but also guarantees the closed-loop stability and constraints satisfaction. Simulation studies are used to investigate the efficiency of the derived method. In this paper, we propose a cross-layer scheduling algorithm that achieves a throughput "epsilon-close" to the optimal throughput in multi-hop wireless networks with a tradeoff of O(1 epsilon) in delay guarantees. The algorithm aims to solve a joint congestion control, routing, and scheduling problem in a multi-hop wireless network while satisfying per-flow average end-to-end delay guarantees and minimum data rate requirements. This problem has been solved for both backlogged as well as arbitrary arrival rate systems. Moreover, we discuss the design of a class of low-complexity suboptimal algorithms, the effects of delayed feedback on the optimal algorithm, and the extensions of the proposed algorithm to different interference models with arbitrary link capacities. We investigate optimal resource allocation for delay- limited cooperative communication in time varying wireless networks. Motivated by real-time applications that have stringent delay constraints, we develop a dynamic cooperation strategy that makes optimal use of network resources to achieve a target outage probability (reliability) for each user subj ect to average power constraints. Using the technique of Lyapunov optimization, we first present a general framework to solve t his problem and then derive quasi-closed form solutions for several cooperative protocols proposed in the literature. Unlike earlier works, our scheme does not require prior knowledge of the statistical description of the packet arrival, channel sta te and node mobility processes and can be implemented in an online fashion.