Channel access protocols for multihop opportunistic networks: challenges and recent developments

Heavy traffic over the unlicensed portion of the spectrum along with inefficient usage of the licensed spectrum gave impetus for a new spectrum allocation policy, the main purpose of which is to improve spectrum efficiency through opportunistic spectrum access. Cognitive radios have been proposed as a key enabling technology for such an opportunistic policy. One of the key challenges to enabling multihop CR communications is how to perform opportunistic medium access control while limiting the interference imposed on licensed users. In this article we highlight the unique characteristics of multihop cognitive radio networks, discuss key MAC design challenges specific to such networks, and present some of the work that has been done on MAC design for CRNs.     

HC-MAC: A Hardware-Constrained Cognitive MAC for Efficient Spectrum Management

Radio spectrum resource is of fundamental importance for wireless communication. Recent reports show that most available spectrum has been allocated. While some of the spectrum bands (e.g., unlicensed band, GSM band) have seen increasingly crowded usage, most of the other spectrum resources are underutilized. This drives the emergence of open spectrum and dynamic spectrum access concepts, which allow unlicensed users equipped with cognitive radios to opportunistically access the spectrum not used by primary users. Cognitive radio has many advanced features, such as agilely sensing the existence of primary users and utilizing multiple spectrum bands simultaneously. However, in practice such capabilities are constrained by hardware cost. In this paper, we discuss how to conduct efficient spectrum management in ad hoc cognitive radio networks while taking the hardware constraints (e.g., single radio, partial spectrum sensing and spectrum aggregation limit) into consideration. A hardware-constrained cognitive MAC, HC-MAC, is proposed to conduct efficient spectrum sensing and spectrum access decision. We identify the issue of optimal spectrum sensing decision for a single secondary transmission pair, and formulate it as an optimal stopping problem. A decentralized MAC protocol is then proposed for the ad hoc cognitive radio networks. Simulation results are presented to demonstrate the effectiveness of our proposed protocol.     

A distributed network coded control channel for multihop cognitive radio networks

Designing a solution for multihop cognitive radio networks poses several challenges such as the realization of the control channel, the detection of primary users, and the coordination of secondary users for dynamic spectrum access purposes. In this article we discuss these challenges and propose a solution that aims to meet most of them. The proposed solution is completely distributed, and does not need dedicated spectrum resources for control purposes, but rather leverages on a virtual control channel that is implemented by having users exchange control information whenever they meet in a particular channel, using network coding techniques for better dissemination performance. Due to these aspects, our proposal represents a significant improvement over existing dynamic spectrum access and multichannel MAC solutions. We discuss the effectiveness of our scheme in multihop cognitive ad hoc networks, where secondary users need to opportunistically access the spectrum at those locations and times at which it is not used by primary users. Finally, we report the results of an evaluation study assessing the performance of the proposed scheme with respect to different system and scenario parameters.     

Spectrum management in cognitive radio ad hoc networks

The problem of spectrum scarcity and inefficiency in spectrum usage will be addressed by the newly emerging cognitive radio paradigm that allows radios to opportunistically transmit in the vacant portions of the spectrum already assigned to licensed users. For this, the ability for spectrum sensing, spectrum sharing, choosing the best spectrum among the available options, and dynamically adapting transmission parameters based on the activity of the licensed spectrum owners must be integrated within cognitive radio users. Specifically in cognitive radio ad hoc networks, distributed multihop architecture, node mobility, and spatio-temporal variance in spectrum availability are some of the key distinguishing factors. In this article the important features of CRAHNs are presented, along with the design approaches and research challenges that must be addressed. Spectrum management in CRAHNs comprises spectrum sensing, sharing, decision, and mobility. In this article each of these functions are described in detail from the viewpoint of multihop infrastructureless networks requiring cooperation among users.     

认知无线Ad Hoc网络中的路由尺度和算法设计

在认知无线Ad Hoc网络中,路由问题面临巨大挑战。由于各认知节点可用频谱的时变性、多样性和差异性,传统的路由尺度不再适用于认知无线Ad Hoc网络。本文在自组织认知网络环境下,应用主用户信道的使用模型,同时考虑次用户之间的干扰情况,提出了两类路由尺度和算法,仿真结果表明,这两类路由尺度都能很好地反映端到端性能。     

多天线认知无线电网络多信道联合频谱感知策略

当前,以单天线认知用户组成的认知无线电网络同时协作检测多个信道的分配策略得到了广泛研究,而在认知用户可以灵活选取自身天线进行空间分集接收的条件下,当联合感知多信道时,多天线认知无线电网络如何获取最优的天线分配策略仍有待进一步研究。为解决这一问题,在限制各信道最大虚警概率的前提下,以最小化所有信道漏检概率之和为目标,建立了优化模型,并提出了基于分支定界的算法和基于贪婪思想的启发式算法。前者可以获得最优策略,但复杂度较高,后者以牺牲较小检测性能为代价,明显降低了复杂度,有效实现了检测性能与复杂度的平衡,并且在保护各个信道上主用户免受认知用户干扰层面,一定程度上兼顾了公平性。      

Optimal Transmission Strategies for Dynamic Spectrum Access in Cognitive Radio Networks

Cognitive radio offers a promising technology to mitigate spectrum shortage in wireless communications. It enables secondary users (SUs) to opportunistically access low-occupancy primary spectral bands as long as their negative effect on the primary user (PU) access is constrained. This PU protection requirement is particularly challenging for multiple SUs over a wide geographical area. In this paper, we study the fundamental performance limit on the throughput of cognitive radio networks under the PU packet collision constraint. With perfect sensing, we develop an optimum spectrum access strategy under generic PU traffic patterns. Without perfect sensing, we quantify the impact of missed detection and false alarm, and propose a modified threshold-based spectrum access strategy that achieves close-to-optimal performance. Moreover, we develop and evaluate a distributed access scheme that enables multiple SUs to collectively protect the PU while adapting to behavioral changes in PU usage patterns. Our results provide useful insight on the trade-off between the protection of the primary user and the throughput performance of cognitive radios.     

Reactive routing for mobile cognitive radio ad hoc networks

Although more than a decade has passed from the proposal of the Cognitive Radio paradigm, in these years the research has mainly focused on physical and medium access issues, and few recent works focused on the problem of routing in cognitive networks. This paper addresses such a problem by evaluating the feasibility of reactive routing for mobile cognitive radio ad hoc networks. More specifically, we design a reactive routing protocol for the considered scenario able to achieve three goals: (i) to avoid interferences to primary users during both route formation and data forwarding; (ii) to perform a joint path and channel selection at each forwarder; (iii) to take advantage of the availability of multiple channels to improve the overall performance. Two different versions of the same protocol, referred to as Cognitive Ad-hoc On-demand Distance Vector (CAODV), are presented. The first version exploits inter-route spectrum diversity, while the second one exploits intra-route spectrum diversity. An exhaustive performance analysis of both the versions of the proposed protocol in different environments and network conditions has been carried out via numerical simulations. The results state the suitability of the proposed protocol for small mobile cognitive radio ad hoc networks.     

Reinforcement-Learning-Based Double Auction Design for Dynamic Spectrum Access in Cognitive Radio Networks

In cognitive radio networks, an important issue is to share the detected available spectrum among different secondary users to improve the network performance. Although some work has been done for dynamic spectrum access, the learning capability of cognitive radio networks is largely ignored in the previous work. In this paper, we propose a reinforcement-learning-based double auction algorithm aiming to improve the performance of dynamic spectrum access in cognitive radio networks. The dynamic spectrum access process is modeled as a double auction game. Based on the spectrum access history information, both primary users and secondary users can estimate the impact on their future rewards and then adapt their spectrum access or release strategies effectively to compete for channel opportunities. Simulation results show that the proposed reinforcement-learning-based double auction algorithm can significantly improve secondary users’ performance in terms of packet loss, bidding efficiency and transmission rate or opportunity access.     

Noncooperative Differential Game Based Efficiency-aware Traffic Assignment for Multipath Routing in CRAHN

Comparing to the traditional multihop ad hoc networks, dynamic spectrum environment is the special characteristic of CRAHN (cognitive radio ad hoc networks). Therefore, the cognitive users will show their selfishness on spectrum bandwidth cost in multihop communication. In CRAHN, multipath routing is a reasonable choice when considering efficiency and stability. In order to take further advantage of efficiency of multipath routing, this paper study the efficiency-awareness traffic assignment problem of multipath routing in CRAHN. There are several existing game based traffic assignment schemes for selfish wireless network, however, all of them can not be directly applicable to CRAHN. In addition, none of the existing works studied whether the scheme is efficient. In this paper, a noncooperative differential game is proposed, and the equilibrium of the game is computed and proved to be an efficient traffic assignment for multipath routing in CRAHN. Besides this, we also optimize the total cost of game from the game designer’s point of view, and give a simple example to illustrate the optimization procedure.     

Integrated Radio Resource Allocation for Multihop Cellular Networks With Fixed Relay Stations

Recently, the notion that a logical next step towards future mobile radio networks is to introduce multihop relaying into cellular networks, has gained wide acceptance. Nevertheless, due to the inherent drawbacks of multihop relaying, e.g., the requirement for extra radio resources for relaying hops, and the sensitivity to the quality of relaying routes, multihop cellular networks (MCNs) require a well-designed radio resource allocation strategy in order to secure performance gains. In this paper, the optimal radio resource allocation problem in MCNs, with the objective of throughput maximization, is formulated mathematically and proven to be NP-hard. Considering the prohibitive complexity of finding the optimal solution for such an NP-hard problem, we propose an efficient heuristic algorithm, named integrated radio resource allocation (IRRA), to find suboptimal solutions. The IRRA is featured as a low-complexity algorithm that involves not only base station (BS) resource scheduling, but also routing and relay station (RS) load balancing. Specifically, a load-based scheme is developed for routing. A mode-aware BS resource-scheduling scheme is proposed for handling links in different transmission modes, i.e., direct or multihop. Moreover, a priority-based RS load balancing approach is presented for the prevention of the overloading of RSs. Within the framework of the IRRA, the above three functions operate periodically with coordinated interactions. To prove the effectiveness of the proposed IRRA algorithm, a case study was carried out based on enhanced uplink UMTS terrestrial radio access/frequency-division duplex with fixed RSs. The IRRA is evaluated through system level simulations, and compared with two other cases: 1) nonrelaying and 2) relaying with a benchmark approach. The results show that the proposed algorithm can ensure significant gains in terms of cell throughput     

Distributed power control algorithm for cognitive radios with primary protection via spectrum sensing under user mobility

Substantial spectrum gains have been demonstrated with the introduction of cognitive radio however; such gains are usually short lived due to the increased level of interference to licensed users of the spectrum. The interference management problem is herein tackled from the transmitter power control perspective so that transmissions by cognitive radio network does not violate the interference threshold levels at the primary users as well as maintain the QoS requirements of cognitive radio users. We model the cognitive radio network for mobile and immobile users and propose algorithms exploiting primary radio environment knowledge (spectrum use), called power control with primary protection via spectrum sensing. The algorithm is briefly introduced for time invariant systems and demonstrated that it has the ability to satisfy tight QoS constraints for cognitive radios as well as meet the interference constraints for licensed users. We, however, further show that such assumption of terminal immobility in the power control algorithm would fail in cases where user mobility is considered, resulting in increased levels of interference to the primary as well as increased outages in cognitive radio network. We model the link gain evolution process as a distance dependent shadow fading process and scale-up the target signal to interference ratio to cope with user mobility. Since mobility driven power control algorithms for cognitive radios have not been investigated before, we therefore, propose a mobility driven power control framework for cognitive radios based on spectrum sensing, which ensures that the interference limit at the primary receiver is unperturbed at all times, while concurrently maintaining the QoS within the cognitive radio network as compared to static user cases. We also corroborate our algorithms with proof of convergence.     

Profit-Based Routing for Multihop Coverage Extension in Wireless Networks

In future wireless systems, the coverage of a base station will decrease due to the characteristics of the channel at high-frequency bands. To expand the service coverage, a hybrid network that combines an ad hoc network with a cellular (or wireless LAN) network, appears to have great potential. In such systems, some mobile users outside the service area can access the network with the aid of other intermediate mobiles. However, this method incurs energy consumption in routing users, which could be a serious obstacle for wide-spread deployment of multihop wireless networks. Therefore we consider a revenue-cost model and propose a profit-based routing strategy that encourages routing users to actively participate in the relaying service because they are compensated for their energy consumption cost. Our strategy enables each mobile node to find an appropriate multihop path to a base station (or access point) that satisfies the interests of the service provider and the users. Numerical results show that our model successfully expands the network coverage area while ensuring the profit of each system involved.     

感知无线电ad hoc网络基于干扰的路由

感知无线电技术作为一种新兴技术,通过时间和空间维度上的频谱空洞的利用能很好地提高频谱利用率。感知无线电的路由不同于传统的路由度量,因为次用户从时间和空间上都不能对主用户造成干扰。在感知无线电ad hoc网络环境下,选取了干扰作为路由的度量,并将干扰分为系统内干扰(次用户自身之间的干扰)和系统间干扰(次用户对主用户的干扰)。在已有的ad hoc网络干扰路由协议的基础上对干扰权重做出改进,并提出新的基于系统间路由干扰(对主用户干扰最小化)和基于联合系统内和系统间干扰的路由协议。仿真结果表明,该干扰模型符合感知无线电移动ad hoc网络的特性。     

Primary user supported routing protocol for cognitive radio ad hoc networks in search of higher throughput

A routing protocol for cognitive radio ad hoc networks (CRAHNs), namely, primary user supported routing (PSR) is demonstrated in this research. Unlike existing routing protocols for CRAHN, where routing of cognitive users (CUs) is accomplished within CUs, in this proposed protocol, some of the primary users (PUs) support CUs to communicate, by forwarding CU packets. This service provided by PU is of voluntary nature. However, such assistance shall be provided by the PUs, only when they are idle, thereby, preserving the principles of cognitive radio networks (CRNs), which indicates that the operation of PU should not be disturbed by the CU activities. The proposed work is compared with cognitive ad hoc on-demand distance vector (CAODV) protocol. The performance parameters considered are routing overhead, rate of loss of packets, and e2e packet delay. PSR outperforms CAODV in all these performance parameters. There has been on average 26.25% improvement in routing overhead, 34.12% decrease in loss, and 27.01% improvement in e2e delivery in the proposed PSR.     

Power Control for Cognitive Radio Networks: A Game Theoretic Approach

In communication industry one of the most rapidly growing area is wireless technology and its applications. The efficient access to radio spectrum is a requirement to make this communication feasible for the users that are running multimedia applications and establishing real-time connections on an already overcrowded spectrum. In recent times cognitive radios (CR) are becoming the prime candidates for improved utilization of available spectrum. The unlicensed secondary users share the spectrum with primary licensed user in such manners that the interference at the primary user does not increase from a predefined threshold. In this paper, we propose an algorithm to address the power control problem for CR networks. The proposed solution models the wireless system with a non-cooperative game, in which each player maximize its utility in a competitive environment. The simulation results shows that the proposed algorithm improves the performance of the network in terms of high SINR and low power consumption.

     

Cognitive radio architecture evolution: annals of telecommunications

Cognitive radio research has developed dynamic radio spectrum management to enhance spectrum efficiency, e.g., as secondary users in unused TV bands. The location and user context of the mobile wireless user that regulatory bodies and lawmakers view as significant to spectrum interference policies have not been addressed as thoroughly. In addition, quality of service (QoS) provides a starting point but does not guarantee quality of experience (QoE) that depends on quality of information (QoI) which is a function of place, time, and user state in a social setting (e.g., commuting, shopping, or in need of medical assistance). This paper considers the evolution of cognitive radio architecture (CRA) from dynamic spectrum access (DSA) to QoE via an interdisciplinary perspective. Machine perception in visual, acoustic, speech, and text domains can cue the automatic detection of user state in stereotypical situations, enabling cognitive nodes and networks to select from among radio bands and modes more appropriately, thus enabling cognitive wireless networks (CWNs) to deliver higher QoE within technical policy constraints, in a way that makes cost-effective use of embedded and distributed computational intelligence. The control of networks of such cognitive radios requires advances in policy language architectures, so this paper introduces cognitive linguistics for policy languages.     

Optimized Ensemble Classifier Based Network Intrusion Detection System for RPL Based Internet of Things

With the increase in user demand for internet access on move, spectrum resource seems to deplete and leads to spectrum crunch. Recent researches reports that this spectrum crunch is not due to spectrum scarcity but due to spectrum underutilization because of legacy static spectrum allocation of spectrum bands. This spectrum utilization and efficiency can be improved by using Dynamic Spectrum Access (DSA) techniques, which correlate with cognitive radio technology in one way or the other. There are three basic approach of communication for cognitive radio technology: Inter-weaved approach, Underlay approach and Overlay approach. Extensive researches has been proposed so far based on the inter-weaved approach and little or negligible using underlay or overlay approach. Using these modes the cognitive users can coexist with the primary users at same geographic time and location. In this paper simple and unique Adaptive Power Control (APC) technique for underlay approach for cognitive radio mobile network is proposed. This techniques introduces a Power Adaptive Transmission (PAT) metric which overcomes three major issues. Firstly, this proposed techniques work efficiently over highly active licensed networks with marginal increased throughput of 0.2 Mbps. Secondly, APC this technique adapts to the requirement of cognitive user and Lastly, primary user power is monitored, to prevent interference and maintain the Quality of Service (QoS) of primary user. Under simulation testing the proposed APC technique outperforms various other underlay as well hybrid techniques for power control under cognitive radio environment with 11% increase in throughput and 32% decrease in delay using APC.

     

认知无线电网络路由及频谱分配联合策略研究

认知无线电网络中的节点可以自主切换通信频率,从而对拓扑和路由产生影响。该文针对多跳认知无线电网络的场景提出了一种路由与频谱分配的联合策略,在按需路由的过程中完成频谱分配任务。实验结果表明,在多数据流并存的认知无线电网络中,该策略较其它路由方法具有更好的适应性和更低的累积时延。     

Applications of Machine Learning to Cognitive Radio Networks

Cognitive radio offers the promise of intelligent radios that can learn from and adapt to their environment. To date, most cognitive radio research has focused on policy-based radios that are hard-coded with a list of rules on how the radio should behave in certain scenarios. Some work has been done on radios with learning engines tailored for very specific applications. This article describes a concrete model for a generic cognitive radio to utilize a learning engine. The goal is to incorporate the results of the learning engine into a predicate calculus-based reasoning engine so that radios can remember lessons learned in the past and act quickly in the future. We also investigate the differences between reasoning and learning, and the fundamentals of when a particular application requires learning, and when simple reasoning is sufficient. The basic architecture is consistent with cognitive engines seen in AI research. The focus of this article is not to propose new machine learning algorithms, but rather to formalize their application to cognitive radio and develop a framework from within which they can be useful. We describe how our generic cognitive engine can tackle problems such as capacity maximization and dynamic spectrum access.