Data aggregation scheduling in wireless networks with Cognitive Radio capability

Transitional Region Phenomenon leads to the existence of lossy links in wireless networks, which results in a transmission between two users who are theoretically connected under the Deterministic Network Model cannot be guaranteed. Therefore, we focus on a more practical network model - Probabilistic Network Model (PNM) which can better characterize the lossy links in wireless networks. To be specific, we focus on the investigation of accelerating data aggregation process in probabilistic wireless networks with the cognitive radio technology. By involving cognitive radio technology, users in the wireless networks can seek extra transmission opportunity if other spectrum resource is available. Otherwise, the data aggregation process still can be done on the default working spectrum. Particularly, we are interested in the time efficient data aggregation scheduling problem. In this work, a two phase scheduling algorithm is proposed. The first phase is finding an efficient routing structure considering the speciality of the network model under investigation. In the second phase, a dynamic scheduling algorithm is introduced. Theoretical analysis is provided to estimate the lower latency bound for the scheduling algorithm, followed by the experimental simulation verification.

With the rapid proliferation of new technologies and services in the wireless domain, spectrum scarcity has become a major concern. The allocation of the Industrial, Medical and Scientific (ISM) band has enabled the explosion of new technologies (e.g. Wi-Fi) due to its licence-exempt characteristic. The widespread adoption of Wi-Fi technology, combined with the rapid penetration of smart phones running popular user services (e.g. social online networks) has overcrowded substantially the ISM band. On the other hand, according to a number of recent reports, several parts of the static allocated licensed bands are under-utilized. This has brought up the idea of the opportunistic use of these bands through the, so-called, cognitive radios and cognitive radio networks. Cognitive radios have enabled the opportunity to transmit in several licensed bands without causing harmful interference to licensed users. Along with the realization of cognitive radios, new security threats have been raised. Adversaries can exploit several vulnerabilities of this new technology and cause severe performance degradation. Security threats are mainly related to two fundamental characteristics of cognitive radios: cognitive capability, and reconfigurability. Threats related to the cognitive capability include attacks launched by adversaries that mimic primary transmitters, and transmission of false observations related to spectrum sensing. Reconfiguration can be exploited by attackers through the use of malicious code installed in cognitive radios. Furthermore, as cognitive radio networks are wireless in nature, they face all classic threats present in the conventional wireless networks. The scope of this work is to give an overview of the security threats and challenges that cognitive radios and cognitive radio networks face, along with the current state-of-the-art to detect the corresponding attacks. In addition, future challenges are addressed.

Both the internet-connected devices, i.e. IoT and Cognitive Radio Network (CRN) are considered to be the future technologies for the fifth generation of cellular wireless standards (5G). On the one hand, Internet of Things (IoT) focuses primarily on how to allow general objects to see, hear, and smell their own physical environment and make them connected to share the observations. On the other hand, a CRN is based on a complex spectrum allocation system, and licenced primary users (PUs) or unlicenced secondary users (SUs) are allowed to share the spectrum, provided they do not cause significant interference. The IoTs are meaningless if IoT objects are not equipped with cognitive radio capability. In cognitive radio, it is important to control the transmission power of SUs so that the interference should not be harmful to the quality of service of PUs. In this paper, the authors addressed the effects of imperfect power control between primary users (PUs) and the secondary users (SUs) of an IoT-based CRN. The effect of the co-channel interference (CCI) and adjacent channel interferences (ACIs) occurring in CRN using MC-CDMA system is also analysed. A new expression of the signal-to-interference-noise ratio (SINR) for CRN-based MC-CDMA system over a Nakagami-[Formula: see text] fading channel with imperfect power control condition is derived and investigated. The performance of IoT-based CRN using MC-CDMA system over the frequency selective multipath fading channel is examined with varying the number of users, the SINR per bit, number of fading path and number of sub-carriers. From the simulation results, we have seen that the SINR performance is affected by these parameters. The result of the analysis will provide relevant information to design the physical layer protocol for high-speed IoT-based CRN system for 5G.

Fractional Link scheduling is one of the most fundamental problems in wireless networks. The prevailing approach for shortest fractional link scheduling is based on a reduction to the maximum-weighted independent set problem, which itself may not admit efficient approximation algorithms. In addition, except for the wireless networks under the protocol interference model, none of the existing scheduling algorithms can produce a link schedule with explicit upper bounds on its length in terms of the link demands. As the result, the polynomial approximate capacity regions in these networks remain blank. This paper develops a purely combinatorial paradigm for fractional link scheduling in wireless networks. In addition to the superior efficiency, it is able to provide explicit upper bounds on the lengths of the produced link schedule. By exploiting these upper bounds, polynomial approximate capacity regions are derived. The effectiveness of this new paradigm is demonstrated by its applications in wireless networks under the physical interference model and wireless MIMO networks under the protocol interference model.

The paper studies throughput-optimal scheduling in wireless networks when there are file arrivals and departures. In the case of single-hop traffic, the well-studied Max Weight algorithm provides soft priorities to links with larger queue lengths. If packets arrive in bursts during file arrival instants, then large variances in file sizes would imply that some links will have very large queue lengths while others will have small queue lengths. Thus, links with small queue lengths may be starved for long periods of time. An alternative is to use only MAC-layer queue lengths in making scheduling decisions; in fact, typically only this information is available since scheduling is performed at the MAC layer. Therefore the questions we ask in this paper are the following: (i) is scheduling using only MAC-layer queue length information throughput-optimal? and (ii) does it improve delay performance compared to the case where scheduling is performed using the total number of packets waiting at a link? We affirmatively answer both questions in the paper (the first theoretically and the second using simulations), making minimal assumptions on the transport-layer window control mechanism.

Channel bonding (CB) is a proven technique to increase bandwidth and reduce delays in wireless networks. It has been applied in traditional wireless networks such as cellular networks and wireless local area networks along with the emerging cognitive radio networks. This paper first focuses on providing a survey of CB schemes for traditional wireless networks such as cellular networks, wireless local area networks, and wireless sensor networks, and then provides a detailed discussion on the CB schemes proposed for cognitive radio networks. Finally, we highlight a number of issues and challenges regarding CB in cognitive radio sensor networks and also provide some guidelines on using CB schemes in these futuristic networks.

We focus on a specific class of denial-of-service (DoS) attacks that is executed through Channel Eviction Triggering (CET), whereby adversary nodes unduly invoke mechanisms inherent in a cognitive radio (CR) network (CRN) operation to protect the licensed users and thus disrupt secondary access to the otherwise idle licensed bands. Skewing the spectrum sensing decision of CRN through sensing misreports is a manifestation of CET attacks. Whereas most studies in the literature focus on making the cooperative sensing more robust against such sensing misreports, we tackle the problem from the novel perspective of incentive alleviation. We distinguish two classes of such DoS attacks, which we refer to as CET and CET-jamming attacks. In the former case, the incentive of adversary CRs is to remove the competition of truthful CRs in accessing the licensed spectral ranges. The latter class of DoS attack deals with scenarios in which the adversary nodes are mainly interested in denying the chances of communication of CRN over primary bands and as such their incentive cannot be modelled by the same utility maximisation model as truthful CRs. We propose a solution for each class of attacks, and our numerical results verify the effectiveness of the proposed CET defence scheme in both cases. Copyright © 2012 John Wiley & Sons, Ltd.

In the existing scenario, the radio spectrum is allocated and divided between unlicensed and licensed frequencies. Due to this policy, some portions of the spectrum remain unused. To cope with this situation, a new communication paradigm is introduced, known as Cognitive Radio (CR). One of the main challenges in Cognitive Radio Network (CRN) is the sharing of spectrum. Spectrum sharing allows several CR nodes for transmission by using vacant spectrum resources. It can be conducted in both distributed and centralized environment. Centralized spectrum sharing can be impractical with the severe increase in spectrum demand. But distributed spectrum sharing along with consumer devices having Cognitive Radio capabilities, provides a realistic spectrum sharing solution. There are three spectrum sharing techniques in dynamic spectrum access (DSA), i.e., underlay, overlay and interweave. Major spectrum sharing challenges are: Common Control Channel and Dynamic Radio Range. There are many other challenging issues still need additional investigations, thus, making Cognitive Radio an open research area. In this chapter, we present a detail survey on different spectrum sharing techniques in CRN. This chapter also presents different performance evaluation parameters to ensure the quality of the spectrum sharing technique. At last it presents various challenges and issues associated with spectrum sharing and the future research opportunities in this area. This will present a clear vision to the young researchers to carry out their research in this domain by knowing the future scope from it.

Cognitive radio network is one of the future technology of wireless communication. Recently, wireless communications are facing the problem of spectrum scarcity due to the huge demand for various applications. There are many applications such as health services, personal entertainment, military and public safety, smart home appliances, smart farming, traffic monitoring, controlling etc., using wireless communication, and most of them are delay sensitive and real time applications. The wireless communication can improve their performance with the capabilities of cognitive radio. In this study, many cognitive radio enabled wireless applications are discussed. It shows that it can be easily deployed with cognitive radio enabled devices without any cost. With this, unused licensed spectrum is utilized efficiently and moreover, it solves the problem of spectrum scarcity.

This paper discusses the topic of wireless security in cognitive radio networks, delineating the key challenges in this area. With the ever-increasing scarcity of spectrum, cognitive radios are expected to become an increasingly important part of the overall wireless networking landscape. However, there is an important technical area that has received little attention to date in the cognitive radio paradigm: wireless security. The cognitive radio paradigm introduces entirely new classes of security threats and challenges, and providing strong security may prove to be the most difficult aspect of making cognitive radio a long-term commercially-viable concept. This paper delineates the key challenges in providing security in cognitive networks, discusses the current security posture of the emerging IEEE 802.22 cognitive radio standard, and identifies potential vulnerabilities along with potential mitigation approaches.

Future wireless networks such as 5G and upcoming 6G require highly efficient resource management to handle massive devices, high data rates, and low-latency applications. Traditional optimisation techniques struggle due to complex traffic patterns and unpredictable wireless environments. This paper explores innovative approaches that use Generative Artificial Intelligence (GAI) — including diffusion models, GANs, and transformers — to optimise spectrum, power, routing, and network scheduling. Generative AI can simulate real network scenarios, create synthetic datasets, design optimal configurations, and support autonomous decision-making. The study highlights how GAI significantly reduces optimisation time, improves network reliability, and lays the foundation for intelligent, self- adaptive wireless systems. Keywords: 6G, generative AI, diffusion models, GANs, VAEs, digital twin, resource allocation, routing, spectrum, ISCC, edge intelligence, intent-driven networking

Wireless Sensor Networks (WSNs) are a class of technology represented with a set of sensor nodes. The main objective of these nodes is to collect data and monitor an environment's events. The basic tasks a node can handle are sensing data (humidity, temperature, fire, etc.), transmitting over short distances, and performing limited data processing. Common WSNs are used in many application fields. The limited resources of the WSNs (low processing capacity, memory and energy reserves) makes them underexploited compared to the WSNs' spectrum utilization. Therefore their applications can be significantly increased by enhancing their performance. To address this challenge, cognitive radio sensor networks (CRSNs) examine how wireless sensor nodes with cognitive radio capabilities can address these performance challenges and improve the spectrum utilization. A new kind of WSN (CRSN) with better performance is created throgh the introduction of cognitive radio to traditional sensor networks. This new class of WSNS is more adapted to some specific applications which require more resources capabilities. In this talk, I will offer a perspective on the emerging field of cognitive radio sensor networks and its current applications.

Driven by the rapidly increasing popularity of Internet-connected phones, tablets and wearable devices, new wireless technologies and standards are emerging at an unprecedented pace. The evolution of wireless networking opens a myriad of possible mobile applications, which have greatly transformed the way we access information, entertain and connect with others. A critical question is how to satisfy the quality of service (QoS) requirements for various applications by delivering the data to users reliably and efficiently under different networking conditions. While many protocols have been proposed for better QoS, they usually requires modification to the networking core or heavy interaction between the layers of the networking stack. Therefore, the goal of dissertation is to develop lightweight, scalable and end-to-end transport solutions to bridge the long-standing gap between the increasing diversity of the mobile applications and the constant evolving wireless technologies. We first focus on studying how to tweak the logic and functionality of traditional TCP protocol given a new wireless networks with different link properties in the context of cognitive radio (CR) network. We start with an extensive ns-3 simulation study of three different classical end-to-end TCP flavors. We conclude that the main adverse impact to the TCP connection in a CR network is the interruption during the transmission period caused by spectrum sensing or primary user arrival events. Based on this insight, we propose TCP C^2, a method that greatly improves the flow responsiveness to abrupt variation of underlying layer spectrum availability in cellular CR architectures. We show that C^2 achieves 2x better throughput compared to TCP NewReno and TCP Westwood+, and approximately 20% improvement in throughput while also incurring 4X shorter queuing delay against Cubic (default implementation in Linux). Our second contribution is Janus, a new transport-layer framework that automatically selects among existing congestion control variants to optimize traffic in accordance with application demands. Janus solves the problem of how to select the right protocol to optimize the QoS for different applications given a large collection of existing TCP variants. We implement Janus in the Linux kernel and extensively evaluate its performance with both emulated and real Internet traffic. Our results show that Janus can significantly improve user-perceived performance according to QoE metrics, with up to 5X fewer interruptions for video streaming applications and 2X faster page loading for web-browsing applications. Finally, we seek to answer the question of how to increase the robustness of data delivery in mmWave networks with densely deployed access points (AP). We conduct real-world experiments with off- the-shelf 60GHz devices and show that naively connecting to any available AP, or even multiple APs, may not fully realize the promise of efficiently utilizing the extremely large bandwidths available in this band. To tackle this problem, we propose Multi-AP Association Protocol (MAP). MAP is a cross-layer connection management mechanism that runs only at the client-side and does not need centralized support from the APs, thus avoiding overheads of added control signaling. We show that MAP can substantially increase the QoS for videostreaming applications for mmWave networks with testbed evaluation and large-scale simulation.

Cognitive radio (CR) has proven to be an excellent alternative to the problem of inefficient spectrum use in wireless networks. However, the vast majority of proposals found in the current literature are restricted to the access of a single secondary user (SU) to the network, and the few proposals with multiple access do not take into account the access of other primary users (PUs) during the opportunistic transmission of the SU. The objective of this work is to perform a comparative evaluation of the spectral handoff (SH) rate in cognitive wireless networks with multi-user access in an environment with other PUs interacting. To carry out this evaluation, four SH models with better performance were selected: deep learning (DL), feedback fuzzy analytic hierarchy process (FFAHP), simple additive weighting (SAW), and Naïve Bayes (NB), which were validated according to the metric of the number of total handoffs, under four scenarios given by the combination of the following parameters: low spectral availability, high spectral availability, active presence of others SUs, and passive presence of others SUs. The results show that each model performs well according to the scenario in which it is executed, suggesting an adaptive multi-model as a proposal.

This paper proposes a spatial time-division multiple access (STDMA) based scheme (STBS) to enhance the system throughput in cognitive radio wireless networks. Especially, the proposed scheme is suitable for the situation when the available number of channels is far less than the number of secondary users (SUs). The system design includes: 1) a novel criterion based on SINR constraint (SC) to determine the feasibility of spatial reuse of spectrum; 2) a heuristic spectrum allocation and scheduling (HSAS) algorithm. Simulation results show that in comparison with the STBS based on Interference range (IR) criterion proposed in [5], the proposed scheme can improve the system throughput as much as 100% when the number of channels is 1/5 of the number of users as well as guarantee a low outage ratio of system blow 2% in various scenarios.