A contention-based wideband DSA algorithm with asynchronous cooperative spectrum sensing

In an opportunistic spectrum access (OSA) based cognitive radio system, a secondary user (SU) is allowed to access the licensed spectrum of the primary user (PU) when it is inactive. Conventional power allocation strategies, which do not consider spectrum sensing information (SSI), may not be optimal in OSA based cognitive radio system because when the SU mis-detects the PU's presence, the interference from the PU will cause a lower data rate or a higher outage probability to the SU. In this paper, power allocation strategies for each frame are designed based on the SSI gathered by the SU during the sensing period of the frame. We consider both cooperative and non-cooperative spectrum sensing scenarios. In non-cooperative spectrum sensing, the SU transmitter (SU-Tx) has its SSI while in cooperative spectrum sensing, the SU-Tx has both its SSI and the SU receiver's (SU-Rx's) SSI. Using the SSIs, power allocation strategies are designed to either maximize the average data rate or minimize the outage probability of the SU. The proposed power allocation strategies have to ensure that the PU is sufficiently protected and the SU satisfies its long-term transmit power budget. Optimization of the sensing time is also considered to further enhance the performances of the system.

Cognitive Radio (CR) technique has been proposed for improving spectrum efficiency by dynamic spectrum access. In Cognitive Radio Networks (CRNs), unlicensed Secondary Users (SUs) with CR can utilize licensed spectrum without interfering licensed Primary Users (PUs). For effectively avoiding interference with licensed PUs and malicious attacks from jammers, a two-stage Learning-based Optimal Channel Selection (LOCS) algorithm for unlicensed SUs in distributed heterogeneous CRNs is proposed in this paper. The LOCS algorithm enables SUs to obtain real states of the licensed channels without knowing their information. Hence, SUs using LOCS algorithm can efficiently avoid collision and attack with PUs and jammers. Besides, the LOCS algorithm considers hardware limitation of the SUs, i.e., SUs can only sense and access parts of the license spectrum during any given time. SUs can select the optimal channels for spectrum sensing and data transmission by using the LOCS algorithm. Simulation results show the efficiency of our proposed algorithm in terms of collision and attack avoidance.

Cognitive radio is an innovative technique for spectrum management which uses Dynamic Spectrum Access (DSA). DSA has the potential to mitigate the spectrum scarcity by letting the Secondary User (SU) access the idle spectrum unused by the Primary User (PU). DSA improves the spectrum efficiency via spectrum sensing and optimal spectrum access. Spectrum sensing should be perfect so that the SU does not cause interference to the PU. Moreover, the channel selected should be the best for maximising throughput of the SU. In this paper we consider a best channel selection problem in Cognitive Radio Networks (CRNs). The problem is modelled as optimal stopping problem where the controller at each state can stop or continue sensing based on the channel gains achieved. There is a Markovian relation given between the channel occupancies of PU. The stopping rule comes out to be simple threshold rule. The controller stops sensing when the channel gain exceeds the given threshold.

Cognitive Radio (CR) aims to provide efficient utilization of the scarcely available radio spectrum. Spectrum sensing is indispensable to identify spectrum holes. Inaccurate sensing results in interference to PU. Therefore, sensing accuracy is an important parameter. Cooperative Spectrum Sensing (CSS) is an efficient technique to improve the sensing accuracy. It makes use of cooperation between Secondary Users (SUs) to detect the presence of Primary User (PU). Game theoretical models help in understanding and modeling interaction among users. In this paper, a CR network with multiple PUs and SUs is considered. CSS is modeled as hedonic coalition formation game where SUs sensing the same channel form coalitions. The coalitions are formed on the basis of probability of detection. For each PU, the SUs which have maximum probability of detection form coalition and cooperatively make the final sensing decision by making use of OR rule. Channel estimation for ST-SR link is done using WARP testbed. The sensing accuracy and energy consumption for the coalitions when link is modeled using free space pathloss model and using WARP testbed are found out. Simulation results show that CSS modeled using hedonic coalition formation has better sensing accuracy than non-cooperative sensing.

Cognitive radio network provides an efficient solution for spectrum utilization. The cooperative spectrum sensing is one of the sensing techniques with which the secondary users of cognitive radio network (CRN) could learn about the availability of the spectrum. In this article, authors had designed and developed their own CRN simulation model in which the RF spectrum range of 54 MHz to 648 MHz is divided into various channels. Secondary users are kept moving in these various channels along with the primary user. The presence of primary user is detected by applying weights on the energy received by local secondary users. The information about the energy of primary user is collected locally by SU and provided to the fusion center for PU detection. This article discusses how the secondary user detects the energy of primary user using weights.KeywordsCognitive radio networks (CRN)Primary users (PU) Secondary users (SU)Dynamic spectrum sensing (DSA)Radio frequency (RF)Cooperative spectrum sensing (CSS) and Fusion center (FC)

A prototype Dynamic Spectrum Access (DSA) system is implemented, for ease of implementation, using the audio spectrum. In this setup, laptop PCs behave as two software defined radios (SDR), one a primary user (PU) and the other a secondary user (SU). The radios communicate digital information over the air, using the audio capabilities of standard soundcards. The PU, which is emulating the licensed user of an audio channel centered at 4 kHz, communicates using binary phase shift keying (BPSK) modulated data in periodic bursts. A cognitive radio (CR) based SU wishes to opportunistically occupy the PU channel during the inter-burst times, i.e. during the temporal ‘spectrum holes,’ while not interfering with the PU traffic. The PU link is implemented in MATLAB, while the SU is defined in GNU Radio with a separate Python control module defining its algorithm for spectrum sensing and hopping. The implementation of both communication links is described, as well as the initial performance evaluation of the preliminary system in terms of bit error rate performance of the PU with and without the presence of an active SU. The measured BER achieved for the best of the PU bursts with DSA was on the order of a few percent, just slightly higher than without DSA.

Dynamic spectrum access has been proposed to address the spectrum scarcity. Based on this access mode, secondary users are allowed to opportunistically operate when primary users are absent. Secondary Users are, however, required to relinquish the spectrum upon return of the incumbent spectrum holder. Although it improves spectrum utility, opportunistic spectrum access limits secondary users' access to exogenous spectrum holes vacated by primary users. We argue that spectrum holes should be endogenous, enabled by incentives to incumbent users to increase spectrum availability, while mitigating risk. To this end, we take a different perspective on dynamic spectrum sharing and propose a coopetive framework, whereby primary and secondary users engage in a cooperative, yet competitive, auction-driven spectrum sharing to enhance spectrum usage. In this framework, the primary users'spectrum is organized in three bands, namely exclusive usage, usage right and management right bands. Based on this structure, spectrum is traded as financial options to increase trading flexibility and capture the value primary and secondary users attach to spectrum access and usage. Spectrum trading between primary and secondary users is formalized as a utility maximization problem. Approximate solutions to this problem are derived and their performance is analyzed. The results show that spectrum trading, which combines revocable and exclusive leasing, provides higher utilities for both primary and secondary users.

The spectrum scarcity problem can be tackled by promoting a more efficient use of the radio spectrum. Spectrum sharing techniques like TV White Spaces (TVWS), Licensed Shared Access (LSA), and Spectrum Access System (SAS), are adequate solutions for this problem and there exist already regulation and standardization efforts worldwide. To evaluate the coexistence between primary and secondary spectrum users, a Long Term Evolution (LTE) multi-cell simulator has been designed, which employs a generic spectrum sharing technique, Dynamic Spectrum Access (DSA), in order to obtain additional network capacity. As a way to bring attention and confidence of the telecommunications sector regarding the benefits that this technology may bring, the analysis is done in terms of interference suffered by incumbents (primary users) and capacity by secondary users. Results have confirmed the unfeasibility of co-channel coexistence for moderate distances between the cordless camera service (incumbent) and LTE network (secondary user) due to high interference. However, for adjacent bands, a gain of 40% in the secondary users’ capacity is possible following more restrictive interference protection requirements and 30% gain with the smaller frequency separation between primary and secondary operating frequencies.

In cognitive radio networks, secondary users need to access the licensed spectrum while neither disturbing the transmissions of the primary users nor introducing much interference to other secondary users. Hence, proper power controlling is of paramount importance to ensure efficient system operation. The previous work on power control in cognitive networks mainly focuses on the interactions among a set of secondary users. The primary users' influence is rarely considered. In this paper, a new power control game model is formulated, by including the primary users into the player set of the game. The primary users are rewarded for sharing their licensed spectrum with secondary users by setting a reasonable interference cap for the secondary transmissions. However, we ensure a minimum required Quality of Service (QoS) for primary users by severely penalizing their utility if their required transmission quality is not met. Simultaneously, the secondary users achieve energy efficient transmissions while not introducing much interference to both the primary and other secondary users. We prove that the proposed cognitive power control game has a unique Nash equilibrium (NE). The numerical examples show that the proposed game theoretical power control algorithm can provide the secondary users with energy efficient transmissions and the primary users with reasonable monetary rewards, while not compromising their required QoS.

Spectrum sensing ranks amongst cognitive radio's most critical and demanding activities. For radio resource networks to use idle licensed bandwidth, secondary users need to identify the primary user's signal precisely. Cognitive radio networks (CRNs) have been proposed to improve the efficiency of spectrum use to meet the increasing demand for wireless bandwidth; they allow channel communication between secondary (unlicensed) and primary (licensed) users without interruption. A secondary user in a CRN must at all times track the presence of a primary user's signal to prevent the primary user (PU) from attempting to intervene whether the statistical variance of the PU data traffic would boost the prediction outcome provided by multiple current teaching algorithms in estimating the PU's average OFF time and the need for the best adaptive learning to predict accurate PU activities. The objective of the work has been modeled to identify the PUs signal. First, the data has been created via quadrature phase shift keying modulation and quadrature amplitude modulation by convolutional neural network (CNN). A dataset with different orthogonal frequency‐division (OFDM) multiple access signals is generated. Then cyclo‐stationary functions are extracted using the accumulation process fast Fourier Transform. This research aims to use glow worm swarm optimization (GWSO) to automatically check for the optimal design of CNNs without any manual work being required. Also, k‐Nearest Neighbors (kNN) replaces Softmax, as it outperforms conventional CNN architectures with noisy signals. A comparison of the proposed classifier with another machine learning classifier, namely support vector machine, Decision tree (DT), clearly shows that SVM and DT are outperformed by the improved convolution neural network‐glow worm swarm optimization (ICNN‐GWSO) classification. Results of simulation show that the improved scheme outperforms conventional spectrum sensing systems, both in fading and non‐fading settings, where efficiency is measured using measures such as chance, the total likelihood of error, and the ability to optimize data transfer possibilities.

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

Cognitive radio (CR) and dynamic spectrum access (DSA) are the effective ways to solve the spectrum congestion problem. Three kinds of basic DSA approaches are respectively dynamic exclusive use, open sharing and hierarchical access. The hierarchical access model is perhaps the most compatible with solving the current spectrum congestion problem. So, in this paper, we will set up an overlay DSA system which is an effective approach of the hierarchical access model. Firstly, we make use of the spectrally modulated spectrally encoded (SMSE) framework to generate OFDM waveforms for the secondary user (SU) which can be considered as the overlay waveform. Then we use the signal which is generated by the walkie-talkie to access the overlay DSA system as a primary user (PU) or an interference signal. The universal software radio peripheral (USRP) and spectrum analyzer are used to generate and analyze the power spectrum density (PSD) of the coexistence of a SU and a PU or an interference signal. The experimental result demonstrates that the overlay DSA system can achieve the function of turning off the sub-carriers corresponding to the frequency of the PU. It also shows that the system can greatly improve the efficiency of the spectrum utilization due to dynamically allocate the spectrum.

Cognitive Radio Networks (CRNs) is a formidable evolution in wireless technology owing to its potentiality to resolve spectrum scarcity crisis. In CRNs, cognitive radio user’s sense idle spectrum as well as opportunistically entrée sensed spectrum devoid of approved users. The best spectrum is said to be selected opportunistically, shared with other users with no severity to licensed users. Many CRN devices that are fueled by battery possessing constrained energy capacity. Prevailing battery mechanisms yet couldn’t contribute CRN devices works for a long time. Therefore, conservation of energy is mandatory as far as routing in CRN is concerned. In this work a machine learning based method called, Regression Cooperative Spectrum Sensing and Gradient Flying Fox Route Optimization (RCSS-GFFRO) for energy and bandwidth aware data routing with spectrum utilization in CRNs is proposed. Protection of primary users (PUs) as well as optimization of secondary user (SU) transmission included in proposed method. In the proposed method a cooperative spectrum sensing using machine learning (ML) model called, Median Regression function is applied. The Median Regression Cooperative Spectrum Sensing in our work with the bandwidth and energy efficiency ensures acceptable probability of interference to primary users due to secondary user’s access by measuring the relationship between bandwidth and energy efficiency simultaneously. Next, optimal route identification is performed using Gradient Flying Fox Route Optimization algorithm. By applying gradient optimization function minimizes the interference with primary users and increases secondary user performance via sensing time and transmission time parameters with higher routing performance. Simulation estimated with parameters.

This paper investigates the use of cooperative spectrum sensing (CSS) to detect primary user (PU) signals during spectrum sharing between the PU and the secondary user (SU). In particular, we employ a variant of CSS (which achieves space diversity), called weighted gain combining CSS (W-CSS), which has the potential to achieve increased diversity gain and enhance detection performance. In a typical W-CSS system, the SU needs to obtain the PU signal power information in order to set the proper weight value. However, as it is hard for the SU to ascertain whether the PU is present or absent, this is difficult to obtain. To address this problem, a PU signal power estimation algorithm is introduced. In addition, we also analyze the statistics of the estimator and derive the detection probability of the W-CSS when the PU signal power estimation algorithm is applied. The analysis and related simulation results reveal that the detection probability of the proposed W-CSS under time-variant Rayleigh fading asymptotically approaches the detection probability in an additive white Gaussian noise channel as the number of antennas is increased. This also follows results from our Monte Carlo simulations, showing that multiple antenna elements could suppress the effect of Rayleigh fading. In short, the accuracy of the estimation algorithm is affected by channel variation (especially in the case of fast Rayleigh fading). Hence, to address this problem, we employ multiple antenna elements with a square-law combining energy detector in the W-CSS. key words: cognitive radio, cooperative spectrum sensing, NeymanPearson theorem, multiple antenna elements

As the novel and effective approach to improving the utilization of the precious radio spectrum, cognitive radio technology is the key to realize the dynamic spectrum access (DSA) networks, where the secondary (unlicensed) users can opportunistically utilize the unused licensed spectrum in a way that confines the level of interference to the range the primary (licensed) users can tolerate. However, there are many new challenges associated with cognitive-radio-based DSA networks, such as the multi-channel hidden terminal problem and the fact that the time-varying channel availability differs for different secondary users, in the medium access control (MAC) layer. To overcome these challenges, we propose an efficient Cognitive Radio-EnAbled Multi-channel MAC (CREAM-MAC) protocol, which integrates the cooperative sequential spectrum sensing at physical layer and the packet scheduling at MAC layer, over the wireless DSA networks. Under the proposed CREAM-MAC protocol, each secondary user is equipped with a cognitive radio-enabled transceiver and multiple channel sensors. Our cooperative sequential spectrum sensing scheme improves the accuracy of spectrum sensing and further protects the primary users. The proposed CREAM-MAC enables the secondary users to best utilize the unused frequency spectrum while avoiding the collisions among secondary users and between secondary users and primary users. We develop the Markov chain model and M/GY/1 queueing model to rigorously study our proposed CREAM-MAC protocol for both the saturation networks and the non-saturation networks. We also conduct extensive simulations to validate our developed protocol and analytical models.