Intelligent and efficient development of wireless networks: A review of cognitive radio networks

Abstract

Facing the challenges on how to improve spectrum efficiency and how to realize heterogeneous network convergence in future wireless networks, a cognitive radio network (CRN) is proposed as one of the solutions. This has become a major research topic in recent years and it is timely to give an overview of the development of CRN and to summarize key issues and technologies. The fundamental concepts of CRN, including the cognitive cycle model, the network architecture, and the cognitive ability and intelligent decision functions, are introduced in detail based on recent advances. Key issues for each topic, followed with recent research on theory and method, are then classified and the industrialization developments of CRN testbeds based on TD-LTE cellular system and standards are briefly presented. Finally, conclusions are reached on the perspectives and directions of future development.cognitive radio networks, network architecture, cognitive ability, spectrum sensing, intelligent decision and dynamic spectrum allocation, end-to-end performance Driven by the requirements of ubiquitous wireless access and personalized wireless applications [1], worldwide, numerous wireless technologies are invading our lives, such as evolutionary telecommunication technologies, wideband wireless access and short distance wireless technologies. Furthermore, the concept of the internet of things (IoT) has become widespread based on the development of wireless sensor networks. With the explosive development of wireless technologies, several challenges must be addressed. The electromagnetic spectrum, whose use is licensed and managed by government, has been scarce for allocation to ubiquitous wireless applications. However, contrary to the physical scarcity of the available spectrum, the report published by the federal communication commission (FCC) shows that over 60 % of the licensed spectrum below 6 GHz remains underused [2,3]. The measurement results in Figure 1 taken in Beijing over a one month period, also indicate low spectrum use consistent with the results released by the FCC. Therefore, improvement of spectrum efficiency is the first challenge to be examined. On the other hand, the end-to-end performance of wireless networks is considered to be the performance indicator for ubiquitous and personalized wireless applications [4], such as end-to-end throughput, end-to-end delay and routing scheme, which take into account all network elements in a data transmission flow across different layers for the global optimization from the network aspect. Because the property of heterogeneity causes low radio resource use and mutual interference among heterogeneous networks, the other big challenge is that heterogeneous network convergence is needed to improve the end-to-end performance of wireless networks.Cognitive radio (CR), proposed by Mitola in 1999 [5,6], is considered a feasible solution for improving spectrum efficiency. Furthermore, a cognitive radio network (CRN), which is defined as a wireless network with the capabilities

Time-Spectrum-Space Three Dimensions Radio Environment Map Construction and Utilization in TV White Space

“…Instead, this paper proposes a greedy algorithm that could achieve the local optimum with guaranteed system performance. If a particular channel-location clustering group is covered by multiple outdoor sensors, outdoor white spaces are determined by comparing the maximum received signal strength to the threshold in (3). WSðC x Þ denotes the white space availability for channel x at all locations, S max ðC x ; L sensors Þ denotes the maximum received signal strength among multiple sensor locations for channel x and WSThr x is the white space threshold.…”

“…As a key technology to utilize TVWS, cognitive radio (CR) technology has been proposed and studied in the literature extensively [2,3]. Rules are defined for the utilization of TVWS by Federal Communications Commission (FCC) with a secondary usage manner in [4].…”

In the development of wireless cognitive science

“…The published articles address a variety aspect of fundamental theory problems and key technology issues in CWN. A review of cognitive radio networks aiming at intelligent and efficient development of wireless networks has been proposed which includes a brief introduction of the network architecture, cognitive abilities, autonomous decision making techniques, testbeds and standards [1]. Moreover, in order to improve the detection performance with multiple secondary users, a fully decentralized cooperative spectrum sensing scheme based on the consensus theory and unsupervised learning technology has been proposed and verified [2].…”

Beijing Spectrum Survey for Cognitive Radio Applications

“…A CR device has the ability to identify an unoccupied spectrum band for temporarily usage, and vacate the spectrum when it is necessary. Therefore, CR is viewed as a technology to overcome the current inefficient usage of radio spectrum resources [3] [4].…”