Cognitive network

About: Cognitive network is a research topic. Over the lifetime, 4213 publications have been published within this topic receiving 107093 citations.

Joint Topology Control and Stable Routing Based on PU Prediction for Multihop Mobile Cognitive Networks

Abstract: Link stability significantly suffers from dynamical primary user activities and random node movement in mobile cognitive networks (MCNs). In multihop MCNs, it will become even worse due to potential interference among multiple links so that stable routing will become more important and also more challenging than that in traditional wireless networks. In this paper, we first formulate the joint topology control and stable routing (JTCSR) problem based on primary user (PU) activity prediction. Then, we propose a PU prediction model to reveal channel utilization patterns of PUs. Next, we propose a novel routing metric PU prediction-based stability metric (PPSM) , which quantitatively measures PU activities and node mobility, and design a min–max PPSM matrix construction algorithm. Finally, we propose and develop a PU prediction-based (PP) JTCSR algorithm for maximizing network throughput, which can find out the most stable and the shortest path. Theoretical analysis validates the effectiveness and efficiency of our approach. NS2-based simulation results further demonstrate that our PP-JTCSR can generate stable and efficient topology through predicting PU activities quantitatively, and outperforms related proposals in terms of path stability, average throughput, and packet loss rate.

Performance Evaluation of Two-Priority Network Schema for Single-Buffered Delta Networks

Abstract: In this paper a novel two-priority network schema is presented, and exemplified through its application on single- buffered Delta Networks in packet switching environments. Network operations considered include conflict resolution and communication strategies. The proposed scheme is evaluated and compared against the single-priority scheme. Performance evaluation was conducted through simulation, due to the complexity of the model, and uniform traffic conditions were considered. Metrics were gathered for the two most important network performance factors, namely packet throughput and the mean time a packet needs to traverse the network. The model can also be uniformly applied to several representative networks providing a basis for fair comparison and the necessary data for network designers to select optimal values for network operation parameters.

Assessing Routing Strategies for Cognitive Radio Sensor Networks

Abstract: Interest in the cognitive radio sensor network (CRSN) paradigm has gradually grown among researchers. This concept seeks to fuse the benefits of dynamic spectrum access into the sensor network, making it a potential player in the next generation (NextGen) network, which is characterized by ubiquity. Notwithstanding its massive potential, little research activity has been dedicated to the network layer. By contrast, we find recent research trends focusing on the physical layer, the link layer and the transport layers. The fact that the cross-layer approach is imperative, due to the resource-constrained nature of CRSNs, can make the design of unique solutions non-trivial in this respect. This paper seeks to explore possible design opportunities with wireless sensor networks (WSNs), cognitive radio ad-hoc networks (CRAHNs) and cross-layer considerations for implementing viable CRSN routing solutions. Additionally, a detailed performance evaluation of WSN routing strategies in a cognitive radio environment is performed to expose research gaps. With this work, we intend to lay a foundation for developing CRSN routing solutions and to establish a basis for future work in this area.

Distributed spectrum assignment for cognitive networks with heterogeneous spectrum opportunities

Abstract: This paper presents a distributed and localized interference-aware channel assignment framework for multi-radio wireless mesh networks in a cognitive network environment. The availability of multiple interfaces and channels in wireless devices is expected to enhance network throughput in wireless mesh networks. A notable design issue in such networks is how to dynamically assign available channels to multiple radio interfaces for maximizing effective network throughput by minimizing interference. The proposed framework uses a novel interference estimation method by utilizing distributed conflict graphs on a per-interface basis. Presented results obtained via simulation studies in 802.11 based multi-radio mesh networks indicate that for both homogeneous and heterogeneous primary networks, the proposed protocol can facilitate a large increase in network throughput in comparison with a Common Channel Assignment mechanism that is used as a benchmark in the literature. Copyright © 2010 John Wiley & Sons, Ltd.

Accelerating software radio: Iris on the Zynq SoC

Abstract: The emergence of cognitive radio and software defined networks are signs of a network world that is much more dynamic. These kinds of systems support reconfiguration of the radio or the network to suit user demands and prevailing conditions so that bandwidth and other resources can be directed to where they are needed. As communication systems become ever more sophisticated, achieving high computational capacity while supporting a high level of flexibility becomes more of a challenge. In this paper we focus on the computational complexity and flexibility that will be required of future cognitive radios. The challenge is to achieve sufficient computational capacity, in particular for processing wide-band high-bitrate waveforms, within acceptable size, weight and power consumption limits while supporting significant flexibility. One method of addressing this problem is through the use of hybrid processing architectures that provide both programmability and performance. In particular we focus on a cognitive radio framework called Iris and explore how Xilinx's Zynq system-on-chip (SoC) can deliver the kind of performance that is needed of future cognitive radio systems. The Zynq SoC has the flexibility offered by an ARM based processing system (PS), while also having performance-orientated programmable logic (PL). The challenges of multi-core programming on embedded platforms and the difficulties of accelerating the cognitive radio functionality in the PL are discussed.