Software-defined routing protocol for mobile cognitive radio networks : a cross-layer perspective

The growing demand for wireless applications, combined with inefficient spectrum use, necessitates developing a new wireless communication paradigm that focuses on dynamic spectrum access rather than the fixed spectrum using cognitive radio technology. The unlicensed user, known as secondary user or cognitive user, uses cognitive radio technology to grow opportunistic communication over licensed spectrum bands and improve spectrum management performance. The routing protocol in Cognitive Radio Networks (CRNs) serves as a communication backbone, allowing data packets to transfer between cognitive user nodes through multiple paths and channels. However, the problem of routing in CRNs is to create a robust-stable route over higher channel availability. The previously developed protocols missed opportunities to exploit the time-variant channel estimation technique, which selects the best route using the cross-layer routing decision engine to track the adverse impact of cognitive user mobility and primary user activity. This study aims to construct a robust routing path while limiting interference with primary user activity, delaying routing, and maximizing routing throughput. Here, a new routing framework is created in this study to explore new extended routing functions and features from the lower layers (Physical layer and Data Link layer) feedback to improve routing performance. Then, the link-oriented channel availability and channel quality have been developed based on two reliable metrics, which are channel availability probability and channel quality, to estimate and select a channel that maximizes link-throughput. Furthermore, this study proposes a novel cross layer routing protocol, namely, the Software-Defined Routing Protocol. It is a cross-layer method to combine the lower layer (Physical layer and Data Link layer) sensing derived from the channel estimation model. It periodically updates the routing table for optimal route decision making. The output simulation of the channel estimation method has shown that it has produced a powerful channel selection strategy to maximize the average rate of link throughput and achieved a channel estimate under the time-variant effect. Extensive simulation experiments have been performed to evaluate the proposed protocol in compression with the existing benchmark protocols, namely, dual diversity cognitive Ad-hoc routing protocol and cognitive Ad-hoc on-demand distance vector. The proposed protocol outperforms the benchmarks, resulting in increasing the packet delivery ratio by around (11.89%-12.80%), reducing delay by around (2.74%-4.05%), reducing overhead by around (14.31%-18.36%), and increasing throughput by around (23.94%-28.35%). The software-defined routing protocol, however, lacks the ability to determine the better idle channel at high-speed node mobility. In conclusion, the cross-layer routing protocol successfully achieves high routing performance in finding a robust route, selecting high channel stability, and reducing the probability of interference with primary users for continued communication

Cross Layer Aware Adaptive MAC based on Knowledge Based Reasoning for Cognitive Radio Computer Networks

In this paper we are proposing a new concept in MAC layer protocol design for Cognitive radio by combining information held by physical layer and MAC layer with analytical engine based on knowledge based reasoning approach. In the proposed system a cross layer information regarding signal to interference and noise ratio (SINR) and received power are analyzed with help of knowledge based reasoning system to determine minimum power to transmit and size of contention window, to minimize backoff, collision, save power and drop packets. The performance analysis of the proposed protocol indicates improvement in power saving, lowering backoff and significant decrease in number of drop packets. The simulation environment was implement using OMNET++ discrete simulation tool with Mobilty framework and MiXiM simulation library.Comment: 8 page

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