Providing QoS in a Cognitive Radio Network

Abstract-We consider the problem of wireless channel allocation (whenever the channels are free) to multiple cognitive radio users in a Cognitive Radio Network (CRN) so as to satisfy their Quality of Service (QoS) requirements efficiently. The CRN base station may not know the channel states of all the users. The multiple channels are available at random times. In this setup Opportunistic Splitting can be an attractive solution. A disadvantage of this algorithm is that it requires the metrics of all users to be an independent, identically distributed sequence. However we use a recently generalized version of this algorithm in which the optimal parameters are learnt on-line through stochastic approximation and metrics can be Markov. We provide scheduling algorithms which maximize weightedsum system throughput or are throughput or delay optimal. We also consider the scenario when some traffic streams are delay sensitive

An Energy Efficient MAC Protocol for QoS Provisioning in Cognitive Radio Ad Hoc Networks

The explosive growth in the use of real-time applications on mobile devices has resulted in new challenges to the design of medium access control (MAC) protocols for ad hoc networks. In this paper, we propose an energy efficient cognitive radio (CR) MAC protocol for QoS provisioning called ECRQ-MAC, which integrate the spectrum sensing at physical (PHY) layer and the channel-timeslots allocation at MAC layer. We consider the problem of providing QoS guarantee to CR users as well as to maintain the most efficient use of scarce bandwidth resources. The ECRQ-MAC protocol exploits the advantage of both multiple channels and TDMA, and achieves aggressive power savings by allowing CR users that are not involved in communication to go into sleep mode. The proposed ECRQ-MAC protocol allows CR users to identify and use the unused frequency spectrum of licensed band in a way that constrains the level of interference to the primary users (PUs). Our scheme improves network throughput significantly, especially when the network is highly congested. The simulation results show that our proposed protocol successfully exploits multiple channels and significantly improves network performance by using the licensed spectrum opportunistically and protects QoS provisioning over cognitive radio ad hoc networks

Green Cellular Networks: A Survey, Some Research Issues and Challenges

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table

Surrogate modeling based cognitive decision engine for optimization of WLAN performance

Due to the rapid growth of wireless networks and the dearth of the electromagnetic spectrum, more interference is imposed to the wireless terminals which constrains their performance. In order to mitigate such performance degradation, this paper proposes a novel experimentally verified surrogate model based cognitive decision engine which aims at performance optimization of IEEE 802.11 links. The surrogate model takes the current state and configuration of the network as input and makes a prediction of the QoS parameter that would assist the decision engine to steer the network towards the optimal configuration. The decision engine was applied in two realistic interference scenarios where in both cases, utilization of the cognitive decision engine significantly outperformed the case where the decision engine was not deployed