A Double Auction Framework for Multi-Channel Multi-Winner Heterogeneous Spectrum Allocation in Cognitive Radio Networks

Empowered by the cognitive radio technology, and motivated by the sporadic channel utilization, both spatially and temporally, dynamic spectrum access networks (also referred to as cognitive radio networks and next generation wireless networks) have emerged as a solution to improve spectrum utilization and provide more flexibility to wireless communication. A cognitive radio network is composed of wireless users, referred to as secondary users, which are allowed to use a given licensed spectrum band as long as there are no primary, licensed, users occupying this band in their vicinity. This restricted spectrum access strategy leads to heterogeneity in channel availability among secondary users. Heterogeneity in channel availability forms a significant source of performance degradation for cognitive radio networks, and poses a great challenge on protocol design. In this dissertation, we propose spectrum allocation algorithms that take this heterogeneity property and its effect on the network performance into consideration. The spectrum allocation solutions proposed in this dissertation address three major objectives in cognitive radio mesh networks. The first objective is maximizing the network coverage, in terms of the total number of served clients, and at the same time simplifying the communication coordination function. To address this objective, we proposed a received based channel allocation strategy that alleviates the need for a common control channel, thus simplifying the coordination function, and at the same time maximizes the number of clients served with link reliability guarantees. We show the superiority of the proposed allocation strategy over other existing strategies. The second objective is improving the multicast throughput to compensate for the performance degradation caused by the heterogeneity in channel availability. We proposed a

The emerging feature-rich and high-data-rate wireless applications have put increasing demand on radio spectrum. The scarcity of spectrum and the inefficiency in its usage, as caused by the current radio spectrum regulations, necessitate the development of new dynamic spectrum allocation policies to better exploit the existing spectrum. The current spectrum allocation regulations assign specific bands to particular services, and grant licensed band access to licensed users only. Cognitive Radio (CR) will revolutionize the way spectrum is allocated. In a CR network, the intelligent radio part allows unlicensed users (secondary users) to access spectrum bands licensed to primary users, while avoiding interference with them. In this scheme, a secondary user can use spectrum sensing hardware/software to locate spectrum portions with reduced primary user activity or idle spectrum slots, select the best available channel, coordinate access to this channel with other secondary users, and vacate the channel when a primary user needs it. To achieve this, the transceiver in a CR system should have awareness of the radio environment in terms of spectrum usage, power spectral density of transmitted/received signals, and wireless protocol signaling, should be able to adaptively tune system parameters such as transmit power, carrier frequency, and modulation strategy. The transceiver should also be ended with an antenna system that can simultaneously operate over a wide frequency band (sensing) and a chosen narrow band (communication), or operate over an ultra-wide frequency band while possibly blocking signals in a narrow frequency range. Ultra-wideband (UWB) is a transmission technique that uses pulses with a very short time duration across a very large frequency portion of the spectrum. UWB is different from other radio frequency communication techniques in that it does not use RF carriers, but instead employs modulated high frequency pulses of low power with a duration of less than 1 nanosecond. From the perspective of other communication systems, the UWB transmissions are part of the low power background noise. Therefore UWB promises to enable the usage of licensed spectrum without harmful interference to primary communication systems, and can be used as an enabling technology for implementing CR. In this chapter, we offer a general overview of Cognitive Radio and dynamic spectrum access, discuss the advantages of using UWB as an enabling technology for CR, and give

This paper considers a cognitive radio (CR) network comprising one cognitive base station (CBS) and a number of secondary users (SUs) that shares a set of channels with a primary network. Both uplink and downlink scenarios are considered in the CR network. The objective is to maximize the throughput of the CR network while protecting the primary transmission and maintaining fairness among the SUs. To fairly allocating resources among the SUs, minimum/maximum number of channels constraint of the SU is introduced to flexibly distribute available channels between the SUs. For both uplink and downlink scenarios, we propose a joint channel allocation and power control scheme. Additionally, a low-complexity two-phase channel allocation and power control scheme is also proposed in the downlink scenario. Simulation results are obtained to validate the performance of the proposed schemes. It is shown that the proposed schemes offer flexibility and controllability in fairly allocating channels to the SUs and yet achieve high throughput. Furthermore, it is shown that the performance gap between the joint scheme and the two-phase scheme is negligible.

With the rapid development of wireless services and applications, the currently radio spectrum is becoming more crowded. How to accommodate more wireless services and applications within the limited radio spectrum becomes a big challenge faced by modern society. Cognitive radio (CR) is proposed as a promising technology to tackle this challenge by introducing secondary users (SUs) to opportunistically or concurrently access the spectrum allocated to primary users (PUs). Currently, there are two prevalent CR models: the spectrum sharing model and the opportunistic spectrum access model. In the spectrum sharing model, the SUs are allowed to coexist with the PUs as long as the interferences from SUs do not degrade the quality of service (QoS) of PUs to an unacceptable level. In the opportunistic spectrum access model, SUs are allowed to access the spectrum only if the PUs are detected to be inactive. These two models known as underlay and overlay schemes, respectively. This thesis studies a number of topics in CR networks under the framework of these two schemes. First, studied cognitive radio transmissions under QoS delay constraints. Initially, we focused on the concept: effective capacity for cognitive radio channels in order to identify the performance in the presence of QoS constraints. Both underlay and overlay schemes are studied taking into consideration the activity of primary users, and assuming the general case of channel fading as Gamma distribution. For this setting, we further proposed a selection criterion by which the cognitive radio network can choose the adequate mode of operation. Then, we studied the cognitive radio transmissions focusing on Rayleigh fading channel and assumed that no prior channel knowledge is available at the transmitter and the receiver. We investigated the performance of pilot-assisted transmission strategies. In particular, we analyzed the channel estimation using minimum mean-square-error (MMSE) estimation, and analyzed efficient resource allocation strategies. In both cases, power allocations and effective capacity optimization were obtained. Effective capacity and interference constraint were analyzed in both single-band and multi-band spectrum sensing settings. Finally, we studied optimal access probabilities for cognitive radio network using Markov model to achieve maximum throughput for both CR schemes.

Cognitive radio (CR) technology allows secondary users (SUs) to share primary user's (PU's) spectrum band by adapting its transmission power in a sensing-based spectrum sharing manner. Spectrum sensing is an important activity in the CR network. Spectrum sensing is used to detect availability of a channel in the PU's spectrum band for the SUs. Presence of attackers such as primary user emulation (PUE) attackers in CR networks imposes some security threats to the SUs which affects the spectrum sensing decisions. In PUE attack, SUs are mislead from using the PU's spectrum band which results in degradation of SU's throughput. To enhance SU's throughput, we have considered hybrid spectrum access scheme with spectrum prediction in this paper. In hybrid spectrum access scheme, the SU switches between overlay or underlay modes based on spectrum sensing decision available at SU. In predictive scheme, the SUs will sense only those channels which are predicted to be idle. Simulation results show that degradation in SU's throughput due to presence of PUE attackers can be compensated by using spectrum prediction in conjunction with hybrid spectrum access.

ABSTRACTThe rapid expansion of the Internet of Things (IoT) and the increasing demand for wireless communication have intensified the need for efficient spectrum management in cognitive radio networks (CRNs). Traditional approaches to spectrum sensing and allocation often operate in isolation or rely on static methods, which fail to address the dynamic and evolving nature of modern wireless environments. As IoT devices proliferate and spectrum resources become increasingly congested, there is a pressing need for more adaptive and efficient spectrum management solutions. Our approach addresses this need by offering an adaptive framework that responds to the changing spectrum landscape, thereby optimizing spectrum usage and reducing interference. This research suggests improved NN joint spectrum sensing for CR‐IoTNet (INJSS‐CR). This approach leverages cognitive radio (CR) technology to enhance spectrum utilization and mitigate the impact of spectrum shortages. CR technology enables secondary users (SUs) to detect and access unused spectrum through spectrum sensing. Within the CR‐IoTNet framework, joint spectrum sensing and allocation are performed to serve SU‐IoT devices via an interference‐free channel (IFC). The system comprises multiple primary user base stations (PU‐BSs) and SU devices functioning as IoT smart objects. Additionally, we integrate an improved neural network (INN) to adapt to dynamic network conditions and monitor primary user (PU) spectrum utilization using a comprehensive multiclass (J × 8) − D feature set. This combination of advanced techniques and CR technology aims to optimize spectrum management and support the growing IoT ecosystem. In particular, the INJSS‐CR obtained the greatest accuracy of 0.9492 at a training rate of 80%.

Opportunistic spectrum access in cognitive radio networks is regarded as solution to spectrum scarcity caused by the static allocation of the frequency spectrum. Unlicensed secondary users (SUs) access the spectrum opportunities which are licensed not licensed to them opportunistically without creating harmful interference to the licensed primary users (PUs). In typical wireless communications, to negotiate and establish a link between transmitter and receiver, common control channel is used. However, attackers can identify the common channel and jam it or overhear and misuse the information. In this paper, we present rendezvous processes for dynamic spectrum access in cognitive wireless networks where transmitter and receiver pair meets in a common channel in an ad hoc manner and establish a link for their communications. Rendezvous processes for dynamic spectrum access provides robust link that prevents any security attacks such as jamming, denial-of-service attack, etc. This paper provides comparison of different rendezvous processes and their applicability in cognitive wireless ad hoc networks.

Motivated by the low utilization of the licensed spectrum across many frequency bands, sensing-based oppor- tunistic spectrum access has recently emerged as an alternative to the outdated exclusive spectrum access policy. Under this new paradigm, a secondary (unlicensed) user monitors a primary (licensed) frequency band for a given and opportunistically transmits if it does not detect any ongoing licensed operations. Evidently, selection of the parameters involves balanc- ing a tradeoff between the speed and the quality with which the secondary user senses the licensed band. With the average throughput as the performance criterion, we obtain the parameters so as to optimize the performance of the secondary user while providing the primary user with its desired level of interference protection. I. INTRODUCTION As evidenced by recent measurements, many frequency bands across the licensed spectrum are significantly under- utilized (1), (2). This finding suggests that the spectrum scarcity, as perceived today, is largely due to the inefficient fixed frequency allocations rather than the physical shortage of the spectrum and has led the regulatory bodies to consider the opportunistic access to the temporally/spatially unused licensed bands (a.k.a. the white spaces) as a means to improve the efficiency of spectrum usage. In the absence of cooperation or signalling between the primary licensee and the secondary users, spectrum availability for the opportunistic access may be determined by direct spectrum where the secondary user monitors a licensed band for a given sensing time and opportunistically transmits if it does not detect any ongoing licensed operations. This approach is particularly appealing due to its low deployment cost and its compatibility with legacy primary users and is being considered for inclusion in the upcoming IEEE 802.22 standard for opportunistic access to the TV spectrum (3). Due to their ability to autonomously detect and to react to the changes in the spectrum usage, secondary users equipped with the spectrum capability may be considered as a primitive form of the cognitive radio (4). Design of any scheme involves balancing a tradeoff between the quality and the speed of through an appropriate selection of the time. As we shall illustrate, in the context of spectrum sensing, may be fine- tuned to enhance the secondary users' perceived quality-of- service (QoS) as long as the regulatory constraint for the protection of the primary users against harmful interference is satisfied. In particular, we will obtain the optimum times at different stages of the spectrum to maximize the average throughput of the secondary user. In this paper, simple energy detection (a.k.a. radiometry) (5) is chosen as the underlying detection scheme. In general, when some information about the structure of the primary signal is available, ad hoc feature-detectors offer a better performance (6). We note, however, that the methodology employed in this paper may be applied to optimize different spectrum sensors once the quality is characterized in terms of the time. The remainder of this paper is organized as follows. The regulatory constraints on spectrum are described in the following section. Section 3 provides an overview of the energy-based spectrum sensing. The optimum times for different stages of the spectrum are derived in Section 4. Finally, this paper is concluded in Section 5.

The rapid increase in the mobile device and the different types of wireless communication has led to the necessity of the extra spectrum allocation for the proper transmission of the information. Since the additional spectrum allocation for every network involved in the data transmission is a strenuous process, the efficient management of the spectrum allocation is preferred. The cognitive radio technology does a befitting service in the managing the allocation of the spectrum efficiently by providing the vacant spaces of the licensed users to the secondary users and vacating the secondary users when the licensed user request for the spectrum. This results in the deterioration in the performance of the secondary users due to the immediate evacuating. The conventional methods in the deciding the channel switching remains unsuitable for the cognitive radio network, so to have an effective decision on switching and selecting the channel the paper put forth the improved fuzzy logic that relies on the decision (IFDSS-GA) support system to handle both the switching of the channels and genetic algorithm to select the proper spectrum for conveyance. The evaluation of the proposed approach using the network simulator -2 determines the competency the IFDSS in terms of the throughput and switching rate.

This paper <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> focuses on spectrum allocation and medium access in future cognitive radio wireless networks, e.g. IEEE 802.22 networks. For a given network topology, the proposed spectrum allocation method first generates an interference graph (or conflict graph) based on the network topology, traffic flows and interference constraints. Then a graph coloring algorithm is applied to the interference graph and the chromatic number of the graph is obtained. This number is the minimum number of distinct spectrum slices required. Further, spectrum allocation is done based on the max-min fair share algorithm or proportional fair algorithm according to the spectrum demands for different spectrum blocks. For medium access among secondary users, we then describe and implement a MAC protocol for 802.22-type cognitive radio networks. Simulation results are presented to demonstrate its effectiveness.

In the recent years Cognitive Radio (CR) technology imposed itself like a very good solution to the increasing spectrum utilization. This technology proposes the development of a new radio type - a cognitive radio - endowed with intelligence that shall sense, share, and use the spectrum opportunities (SOP) of the preexisting wireless networks, that is the channels that are not used by the licensed users. A new routing algorithm for CR networks (CRN): IPSAG - IP Spectrum Aware Geographic based Routing Protocol is presented in the paper. As suggested by the name, the IP hop-by-hop, the geographic, and the spectrum aware routing concepts were used together in the protocol's design. The dynamism and flexibility, characteristic to both CR and IP networks, made us compare the CR concept with the IP concept (a wireless versus wired flexible environment comparison); thus we assumed the IP routing approach for CRN. The proposed strategy is based on hop-by-hop routing, local decisions being taken by nodes according to both local information (CR node's neighborhood) and global information (the entire topology of CRN), channels availability, and destination location.

Cognitive radio networks (CRN) is a promising technology for the efficient utilization of spectrum resource. However, how to dynamically allocate the spectrum combining with the characteristics of CRN is a crucial challenge for the mechanism design. In this paper, from the perspective of frequency-time characteristics of the spectrum opportunity in CRN and the secondary users' flexible requirements, we model the dynamic spectrum allocation problem as a knapsack problem and prove that maximizing the social welfare is NP-hard. Therefore, a spectrum auction mechanism is developed to approximate the optimal social welfare, and we prove its approximate ratio. Further, to guarantee the truthfulness, we devise a corresponding payment scheme. In simulation results, we show that no matter how many SUs are in the CRN, our scheme can approximate the maximal social welfare perfectly, and the spectrum utilization can be improved to over 96.5% or even larger.

The optimal admission control for secondary users (SUs) using blockchain technology in a cognitive radio (CR) network is investigated in this paper. When an SU comes to the system, it will decide to either enter the system, or give up its service and then leave the system based on the current number of PU and SU users in the network. SUs are linked as a block in the waiting area to access the spectrum in an opportunistic way without interfering the operations of PUs. When a PU arrives, if the band is occupied by SU(s), the SU service on the band is interrupted and SU(s) is then placed back to the waiting queue. Admitting an SU would bring a reward to the system provider but holding an SU in the system would also incur an expense to the provider. We concentrate on the optimization problem of when to admit or reject an arriving SU in order to achieve the maximum total discounted expected reward for any initial state. By establishing a discounted Continuous Time Markov Decision Process (CTMDP) model, we verify that the optimal policies for admitting SUs are state-related control limit policies. An extensive numerical analysis is implemented to show how to determine the value of optimal threshold and of the corresponding maximum objective function. Especially, a simulation by using the idea of the neural network and machine learning is implemented to show how to determine the optimal threshold value for any new input parameters through learning process for a given input parameters. The idea and the corresponding result of this paper can be applied in designing optimal cognitive radio networks.

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.

In this paper, we consider medium access control (MAC) protocol design for random-access cognitive radio (CR) networks. A two-level opportunistic spectrum access strategy is proposed to optimize the system performance of the secondary network and to adequately protect the operation of the primary network. At the first level, secondary users (SUs) maintain a sufficient detection probability to avoid interference with primary users (PUs), and the spectrum sensing time is optimized to control the total traffic rate of the secondary network allowed for random access when the channel is detected to be available. At the second level, two MAC protocols called the slotted cognitive radio ALOHA (CR-ALOHA) and cognitive-radio-based carrier-sensing multiple access (CR-CSMA) are developed to deal with the packet scheduling of the secondary network. We employ normalized throughput and average packet delay as the network metrics and derive closed-form expressions to evaluate the performance of the secondary network for our proposed protocols. Moreover, we use the interference and agility factors as the performance parameters to measure the protection effects on the primary network. For various frame lengths and numbers of SUs, the optimal performance of throughput and delay can be achieved at the same spectrum sensing time, and there also exists a tradeoff between the achievable performance of the secondary network and the effects of protection on the primary network. Simulation results show that the CR-CSMA protocol outperforms the slotted CR-ALOHA protocol and that the PUs' activities have an influence on the performance of SUs for both the slotted CR-ALOHA and CR-CSMA.