Queuing regime is one outstanding approach in improving channel aggregation. If well designed and incorporated with carefully selected parameters, it enhances the smooth rollout of fifth/next generation wireless networks. While channel aggregation is the merging of scattered TV white space (spectrum holes) into one usable chunk for secondary users (SU). The queuing regime ensures that these unlicensed users (SUs) traffic/ services are not interrupted permanently (blocked/dropped or forced to terminate) in the event of the licensed users (primary user) arrival. However, SUs are not identical in terms of traffic class and bandwidth consumption hence, they are classified as real time and non-real time SU respectively. Several of these strategies have been studied considering queuing regime with a single feedback queuing discipline. In furtherance to previous proposed work with single feedback queuing regime, this paper proposes, develops and compares channel aggregation policies with two feedback queuing regimes for the different classes of SUs. The investigation aims at identifying the impacts of the twofeedback queuing regime on the performance of the secondary network such that any SU that has not completed its ongoing service are queued in their respective buffers. The performance is evaluated through a simulation framework. The results validate that with a well-designed queuing regime, capacity, access and other indices are improved with significant decrease in blocking and forced termination probabilities respectively.
In this paper, a filtering stage based on employing a Savitzky-Golay (SG) filter is proposed to be used in the spectrum sensing phase of a Cognitive Radio (CR) communication paradigm for Vehicular Dynamic Spectrum Access (VDSA). It is used to smooth the acquired spectra, which constitute the input for a spectrum sensing algorithm. The sensing phase is necessary, since VDSA is based on an opportunistic approach to the spectral resource, and the opportunities are represented by the user-free spectrum zones, to be detected through the sensing phase. Each filter typology presents peculiarities in terms of its computational cost, de-noising ability and signal shape reconstruction. The SG filtering properties are compared with those of the linear Moving Average (MA) filter, widely used in the CR framework. Important improvements are proposed.
A novel method to improve the performance of the frequency band is cognitive radio that was introduced in 1999. Due to a lot of advantages of the OFDM, adaptive OFDM method, this technique is used in cognitive radio (CR) systems, widely. In adaptive OFDM, transmission rate and power of subcarriers are allocated based on the channel variations to improve the system performance. This paper investigates adaptive resource allocation in the CR systems that are used OFDM technique to transmit data. The aim of this paper is to maximize the achievable transmission rate for the CR system by considering the interference constraint. Although secondary users can be aware form channel information between each other, but in some wireless standards, it is impossible for secondary user to be aware from channel information between itself and a primary user. Therefore, due to practical limitation, statistical interference channel is considered in this paper. This paper introduces a novel suboptimal power allocation algorithm. Also, this paper introduces a novel bit loading algorithm. In the numerical results sections, the performance of our algorithm is compared by optimal and conventional algorithms. Numerical results indicate our algorithm has better performance than conventional algorithms while its complexity is less than optimal algorithm.
Faithfull detection of non-utilized spectrum hole in available channel is a crucial issue for cognitive radio network. Choosing the best available channel for a secondary user transmission includes settling on decision of accessible choices of free frequency spectrum based on multiple objectives. Thus channel judgment can be demonstrated as several objective decision making (MODM) problem. An ultimate goal of this exploration is to define and execute a technique for multiple objective optimizations of multiple alternative of channel decision in Adhoc cognitive radio network. After a coarse review of an articles related to the multiple objective decision making within a process of channel selection, Multiple Objective Optimization on the basis of the Ratio Analysis (MOORA) technique is taken into consideration. Some important objectives values of non-utilized spectrum collected by a fusion center are proposed as objectives for consideration in the decision of alternatives. MOORA method are applied to a matrix of replies of each channel alternatives to channel objectives which results in set ratios. Among the set of obtained dimensionless ratios, all the channel alternatives are ranked in descending order. In MOORA, channel choices with moderate objectives can top in ranking order, which is hardly conceivable with linearly weighted objectives of the different channel by using different decision making technique.
This article investigates and evaluates a handover exchange scheme between two secondary users (SUs) moving in different directions across the handover region of neighboring cell in a cognitive radio network. More specifically, this investigation compares the performance of SUs in a cellular cognitive radio network with and without channel exchange scheme. The investigation shows reduced handover failure, blocking, forced and access probabilities respectively, for handover exchange scheme with buffer as compared to exchange scheme without buffer. It also shows transaction within two cognitive nodes within a network region. The system setup is evaluated through system simulation.
A novel non-orthogonal multiple access (NOMA) scheme is proposed to improve the throughput and the outage probability of the cognitive radio (CR) inspired system which has been implemented to adapt multiple services in the nextgeneration network (5G). In the proposed scheme, the primary source (PS) had sent a superposition code symbol with a predefined power allocation to relays, it decoded and forwarded (DF) a new superposition coded symbol to the destination with the other power allocation. By using a dual antenna at relays, it will be improved the bandwidth efficiency in such CR NOMA scheme. The performance of the system is evaluated based on the outage probability and the throughput with the assumption of the Rayleigh fading channels. According to the results obtained, it is shown that the outage probability and throughput of the proposed full-duplex (FD) in CR-NOMA with reasonable parameters can be able deploy in practical design as illustration in numerical results section.
In this study, an energy-based spectrum sensing method combined with copula theory is proposed for cognitive radio systems. In the proposed spectrum sensing model, cognitive radio users first make their own local spectrum decision with energy-based spectrum sensing. Then, they forward their decision to the fusion center. In the fusion center, this decision is compared with the threshold value determined by copula theory and global spectrum decision is made. The test statistic at the fusion center were obtained with the Neyman Pearson approach. Thus, the fusion rule was created for the fusion center and necessary simulation studies were performed. According to the results of the simulation studies, the proposed detection method showed better results than the traditional energy based detection method.
In this paper, the future Fifth Generation (5G New Radio) radio communication system has been considered, coexisting and sharing the spectrum with the incumbent Fourth Generation (4G) Long-Term Evolution (LTE) system. The 4G signal presence is detected in order to allow for opportunistic and dynamic spectrum access of 5G users. This detection is based on known sensing methods, such as energy detection, however, it uses machine learning in the domains of space, time and frequency for sensing quality improvement. Simulation results for the considered methods: k-Nearest Neighbors and Random Forest show that these methods significantly improves the detection probability.