Cognitive Ad Hoc Networks Research Articles

Spectrum Handoff Aware AODV Routing Protocol for Cognitive Radio Vehicular Ad Hoc Networks

End-to-end application performance and throughput of vehicular cognitive transport control protocol depend on how efficiently the segments (TCP header) are being transmitted from source to destination. One way to enhance the performance of vehicular cognitive TCP protocol is by reducing the packet drops in between the source and destination. In general, packet drops occur in between the source and destination of Cognitive Radio Vehicular Ad Hoc Network (CR-VANET) because of spectrum handoff or cognitive node handoff, or network congestion. In this paper, we focus on enhancing the performance of cognitive TCP protocol through “cognitive AODV routing protocol with the spectrum handoff mechanism.” In the proposed work, channel-route control messages of cognitive AODV routing protocol are updated with the support of spectrum handoff which helps to provide the backup opportunistic channel during PU active and helps to reduce the end-to-end spectrum handoff packet drops. Simulation results reveal that the overall performance of the vehicular cognitive TCP protocol with the proposed spectrum handoff aware cognitive AODV routing protocol is enhanced as compared to the existing cognitive TCP protocol.

Distributed Resource Allocation for SWIPT-Based Cognitive Ad-Hoc Networks

Energy supplies, spectrum resources, and transmission overheads of wireless nodes are the bottlenecks in decentralized networks (e.g., device-to-device communication networks). In this paper, we study the total power minimization problem of secondary users (SUs) for a multiuser simultaneous wireless information and power transfer-based cognitive ad-hoc network by jointly optimizing the transmit power and power-splitting (PS) coefficients of SUs in a distributed way, where SUs can harvest ambient radio-frequency signals to prolong the lifetime of nodes via a PS-based scheme. Firstly, a resource allocation (RA) problem with perfect channel state information (CSI) is formulated under the quality of service constraints and the minimum energy-harvesting (EH) constraints. The non-convex problem is decomposed into a subproblem with a high EH threshold and a subproblem with a low EH threshold. The distributed closed-form solutions are obtained via Lagrange dual theory. Secondly, to overcome the impact of channel estimation errors, a robust RA problem with imperfect CSI is studied under bounded uncertainties. Both the feasible region and robust sensitivity are analyzed to give an insight into system performance. Simulation results demonstrate that the effectiveness of the proposed algorithm.

Interference resilient stochastic prediction based dynamic resource allocation model for cognitive MANETs

Background/Objectives: Being dynamic in nature, Mobile Ad-hoc Network (MANET) requires robust resource allocation strategy that can ensure both optimal transmission reliability and resource efficiency to meet Quality of Service (QoS) demands. The objective of this research is to address interference resilience requirement in MANETs which is must due to greedy nature of nodes especially when accessing resource or bandwidth and develop a highly robust stochastic prediction based resource allocation strategy. Methods: The proposed Interference Resilient Stochastic Prediction based Dynamic Resource Allocation model for Cognitive MANET (ISP-DRACM) intends to enable optimal resource allocation under interweave and underlay network setup with instantaneous as well as average interference conditions. It employs a joint power management and resource allocation strategy where it intends to maximize the weighted sum-rate of the secondary users under certain defined conditions like average power and stochastic interference level. Findings/Novelty: Inculcating resource allocation problem as controlled Markov Decision Process using Hidden Markov Model (HMM) and Lagrange relaxation, our proposed model achieves better resource allocation under limited noise or interference condition and hence achieves both costeffectiveness as well as QoS provision. This method has exhibited satisfactory performance towards spectrum allocation to the secondary users without imposing any significant interference for both interweave as well as underlay Cognitive Radio setup. Keywords: Cognitive mobile ad-hoc network; stochastic prediction; interference resilience; channel state information; dynamic resource allocation; underlay and overlay cognitive MANET

Probabilistic Selective Broadcast for energy-saving communications in Cognitive Ad Hoc Networks

Cognitive radio, as a promising technology, plays an important role in ad hoc network communications, leading to more reasonable and orderly utilizations of wireless spectrum resources. It is not only an opportunity but also a challenge for wireless mobile communications. In cognitive radio ad hoc networks, the non-uniform channel arrays available for secondary users make difficult to the application of broadcasting technologies, concentrating on common channel selection and broadcast collision. In this paper, a probabilistic selective broadcast, called pSB, is proposed, aiming at economy and energy-saving distributed wireless communications. The protocol adopts an intelligent channel selection policy with a probabilistic forwarding strategy to alleviate collisions caused by redundant message exchanges. Consequently, the proposed pSB outperforms other methods in terms of higher message reach rates and fewer broadcast collisions evaluated by simulations under different parameter configurations.

인지 무선 모바일 애드혹 네트워크를 위한 다중 메트릭 기반 멀티 홉 클러스터링 기법

최근 애드 혹 네트워크 환경에서 인지 무선 기술에 대한 연구가 활발히 진행되고 있는데 특히, 효율적인 네트워킹을 위해 가용 주파수 채널을 기반으로 한 클러스터링 기법들이 제안되었다. 그러나, 기존 연구들에서는 모바일애드 혹 네트워크의 특성(단말의 이동성, 홉 수에 따른 성능저하 등)이 크게 고려되지 않은 채 가용 채널의 상태만을 고려하여 클러스터를 형성하기 때문에 빈번한 클러스터 재구성 및 이에 따른 통신 안정성 저하, 네트워크 유지보수 오버헤드 문제가 발생한다. 본 논문에서는 이러한 문제를 해결하기 위해 가용 채널의 개수와 더불어 단말의 위상 정보 및 이동성 정보 등을 바탕으로 클러스터를 구성하도록 하는 기법을 제안한다. 시뮬레이션을 통해 성능검증 결과, 기존 연구들 대비 클러스터링 오버헤드와 통신비용에서 향상된 성능 결과를 보이는 것을 확인하였다.

Distributed Learning in Ad-Hoc Networks with Unknown Number of Players

We study algorithms for distributed learning in ad-hoc cognitive networks where no central controller is available. In such networks, the players cannot communicate with each other and even may not know how many other players are present in the network. If multiple players select a common channel they collide, which results in loss of throughput for the colliding players. We consider both the static and dynamic scenarios where the number of players remains fixed throughout the game in the former case and can change in the later. We provide algorithms based on a novel 'trekking approach' that guarantees with high probability constant regret for the static case and sub-linear regret for the dynamic case. The trekking approach gives improved aggregate throughput and also results in fewer collisions compared to the state-of-the-art algorithms.

Cog-MAC Protocol: Channel Allocation in Cognitive Ad Hoc Networks Based on the Game of Learning Automata

Spectrum allocation is a major challenge in wireless ad hoc networks due to restrictions on the number of available communication channels and also passive approaches to channel allocation in dealing with changes in the network environment, and it is impossible to achieve a perfect operational status, which includes a comprehensive communication. Adding cognition to current networks enables them to plan, learn, and reason, and also enables network nodes to self-adapt themselves to their surroundings and to adjust the required bandwidth to perform their operations. This paper introduces a cognitive ad hoc network with two cognitive elements with the aim of improving the use of wireless spectrum. These elements are placed at each node of the network. One element predicts the traffic at each node using neural networks, and the other solves the problem of channel allocation according to this predicted traffic using a non-cooperative game of learning automata and the techniques for allocating variable-width channels. Then, an analysis is done on the convergence of the algorithm and achieving the Nash equilibrium in the game. The purposes of the proposed algorithm are efficient spectrum use, reducing interference, and achieving the ultimate goals of the network, which are quality of service parameters such as high throughput and low latency. Simulation results showed the superior performance of the proposed algorithm compared to alternative approaches.

Delay-Minimized Routing Protocol for Mobile Cognitive Ad-Hoc Networks

Delay-Minimized Routing Protocol for Mobile Cognitive Ad-Hoc Networks

Towards low-delay and high-throughput cognitive radio vehicular networks

Abstract Cognitive Radio Vehicular Ad-hoc Networks (CR-VANETs) exploit cognitive radios to allow vehicles to access the unused channels in their radio environment. Thus, CR-VANETs do not only suffer the traditional CR problems, especially spectrum sensing, but also suffer new challenges due to the highly dynamic nature of VANETs. In this paper, we present a low-delay and high-throughput radio environment assessment scheme for CR-VANETs that can be easily incorporated with the IEEE 802.11p standard developed for VANETs. Simulation results show that the proposed scheme significantly reduces the time to get the radio environment map and increases the CR-VANET throughput.

Joint Routing and Scheduling in Cognitive Radio Vehicular Ad Hoc Networks

Joint Routing and Scheduling in Cognitive Radio Vehicular Ad Hoc Networks

Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays

It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.

Mobility Prediction Based Joint Stable Routing and Channel Assignment for Mobile Ad Hoc Cognitive Networks

Link instability and channel interference cause significant performance degradation to mobile ad hoc cognitive networks (MACNets). Existing work designs routing and assigns channels separately or does not consider mobility prediction and channel vacation to primary nodes. In this paper, we investigate how to jointly optimize route setup and channel assignment. Firstly, we propose an integrated data transmission cost (IDTC) to quantitatively measure the communication quality of links. This novel routing metric IDTC integratively considers 1) node mobility, 2) co-channel interference among primary and cognitive nodes, 3) relay workload on a specified channel, and 4) distance between the relay and the destination node. We, then, design channel assignment algorithms that completely avoid the interference with primary nodes and minimize the conflict to cognitive nodes. Finally, we propose a joint stable routing and channel assignment (J-SRCA) protocol based on mobility prediction for the network throughput maximization. In our J-SRCA, each link selected hop by hop is simultaneously assigned an interference-avoiding channel during a route setup. NS2-based simulation results demonstrate that our J-SRCA significantly improves various network performance, and the higher interference degree cognitive networks experience, the more improvement our J-SRCA will bring to the networks.

Frequency Hopping CR MAC Protocol in Cognitive Radio Ad Hoc Network

To insure the fairness for the Cognitive Radio (CR) nodes with various available channels, a frequency hopping CR MAC protocol based dynamic (named DCR-MAC) is proposed. In the case of uneven distribution of frequency spectrum in cognitive Ad Hoc network, based on the numbers of workable channels of each cognitive node, DCR-MAC protocol adjusts access time dynamically, ensuring the node priority access channel number, in order to improve the overall performance of the network. Meanwhile, against the problem of the multi-channel hidden terminal which appears in cognitive network of single wireless interface configuration, through introducing the segment mechanism, and informing present channels occupied condition of adjacent node via receiving node, DCR-MAC protocol broadcast of channel occupation in transmission channel, and prohibit possible data transmission of adjacent node, in order to solve this problem on this account. Finally, proving that DCR-MAC protocol is obviously excelled other FH CR MAC protocols in through put capacity, packet access delay, accessing fairness which through network simulation.

Routing Protocol of Cognitive Ad Hoc Network

Routing Protocol of Cognitive Ad Hoc Network

Performance Evaluation of Data Delivery Mechanism For Cognitive Radio Vehicular and Vehicular Ad-Hoc Networks

Recently, the Vehicular Networks are gaining increased attention for generating extensive wireless communication. They are also integrated with Cognitive Radio to further enhance their performance. However the guaranteed delivery of data is an important parameter for evaluating these networks. This paper provides a simple, but nevertheless extremely accurate, simple model to evaluate the performance of both Vehicular Ad-hoc and Cognitive Radio Vehicular Networks. The proposed analysis applies to both the networks on the basis of various parameters like delay, packet loss, packet drop ratio, throughput using extensive simulation. The results validate the assumption that Cognitive Vehicular Radios outperform the” VANET's when various types of packets are transmitted using V2 V communication.

CARC: A Reliable Routing Mechanism for Cognitive Ad Hoc Networks

CARC: A Reliable Routing Mechanism for Cognitive Ad Hoc Networks

Learning System for Proactive Pre-emptive Unified Spectrum Handoff (PRO-PUSH) in Cognitive Radio Mobile Ad Hoc Networks

The aim of this study is to introduce a conceptual framework for the new approach Intelligent Proactive Pre-emptive Unified Spectrum Handoff (IP PRO-PUSH) algorithm is presented, which is a highly potential intelligent technology to intelligently address the spectrum scarcity challenges in Cognitive Radio Mobile Ad hoc Networks (CR-MANETs). The fact that spectrum is a limited natural resource poses technology challenge to ensure the available frequency is used efficiently and able to cope with new services which definitely requires more bandwidth in the future. However, over the past years, traditional approaches to spectrum management have been challenged by new insights into actual use of spectrum. In order to improve the utilization of the overall radio spectrum, the Cognitive Radio (CR) is a useful solution to this low utilization of the radio spectrum. The variation in spectrum band is called spectrum mobility. The objective of the current study is to investigate the Intelligent-Based (IB) cognitive radio learning for IP Pro-PUSH and local routing based on spectrum mobility in mobile Cognitive Radio Ad hoc Networks (CR-MANET) along with a conceptual framework and its connections.

Transmission Power-Based Spectrum Sensing for Cognitive Ad Hoc Networks

In spectrum sensing, there is a tradeoff between the probability of missed detection and the probability of a false alarm according to the value of the sensing threshold. Therefore, it is important to determine the sensing threshold suitable to the environment of cognitive radio networks. In this study, we consider a cognitive radio-based ad hoc network where secondary users directly communicate by using the same frequency band as the primary system and control their transmit power on the basis of the distance between them. First, we investigate a condition in which the primary and the secondary users can share the same frequency band without harmful interference from each other, and then, propose an algorithm that controls the sensing threshold dynamically on the basis of the transmit power of the secondary user. The analysis and simulation results show that the proposed sensing threshold control algorithm has low probabilities of both missed detection and a false alarm and thus, enables optimized spectrum sharing between the primary and the secondary systems.

A Joint Design for Distributed Stable Routing and Channel Assignment Over Multihop and Multiflow Mobile Ad Hoc Cognitive Networks

Data communication in mobile ad hoc cognitive networks (MACNets) significantly suffers from link instability and channel interference. The availability and stability of each link in MACNets highly depends on not only the relative movement of neighbor nodes but also the adjacent communication among primary nodes and among cognitive nodes. In multihop and multiflow MACNets, this problem becomes even worse because multiple links potentially interfere with each other. In this paper, we propose a cross-layer distributed approach, called mobility-prediction-based joint stable routing and channel assignment (MP-JSRCA), to maximize the network throughput by jointly selecting stable routes and assigning channels avoiding inter- and intra-flow interferences based on mobility prediction. To quantitatively measure the communication quality of links, we propose a new metric data transmission cost (DTC) that captures node mobility, impact to primary nodes, and channel conflict among cognitive nodes. In our MP-JSRCA, each relay node selects the best link with the smallest DTC as the next hop, within a specified sector region towards the destination. NS2-based simulation results demonstrate that our MP-JSRCA algorithm significantly improves network throughput, and the higher degree of interference MACNets experience, the more improvement can be achieved.

CAD-MAC: A Channel-Aggregation Diversity Based MAC Protocol for Spectrum and Energy Efficient Cognitive Ad Hoc Networks

In cognitive Ad Hoc networks (CAHN), because the contentions and mutual interferences among secondary nodes are inevitable as well as secondary nodes usually have limited power budget, spectrum efficiency and energy efficiency are critically important to the CAHN, especially for the medium access control (MAC) protocol design. Aiming at improving both spectrum and energy efficiencies, we in this paper propose a diversity technology called Channel-Aggregation Diversity (CAD), through which each node can utilize multiple channels simultaneously and efficiently allocate the upper-bounded power resource with only one data radio. Based on the proposed CAD technology, we further develop a CAD-based MAC (CAD-MAC) protocol, which enables the secondary nodes to sufficiently use available channel resources under the upper-bounded power and transmit multiple data packets in one transmission process subject to the transmission-time fairness constraint. In order to improve the performance of CAHNs, we propose two joint power-channel allocation schemes. In the first scheme, we aim at maximizing the data transmission rate. By converting the joint power-channel allocation to the Multiple-Choice Knapsack Problem, we derive the optimal allocation policy through dynamic programming. In the second scheme, our objective is to optimize the energy efficiency and we obtain the corresponding allocation policy through fractional programming. Simulation results show that our proposed CAD-MAC protocol can efficiently increase the spectrum and energy efficiencies as well as the throughput of the CAHN compared with existing protocols. Moreover, the energy efficiency of the CAHN can be further improved by adopting the energy efficiency optimization based resource allocation scheme.