• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.197-199
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• 2016

In this paper, we investigate a market equilibrium in multi-channel sharing cognitive radio networks (CRNs): it is assumed that every subchannel is orthogonally licensed to a single primary user (PU), and can be shared with multiple secondary users (SUs). We model this sharing as a spectrum market where PUs offer SUs their subchannels with limiting the interference from SUs; the SUs purchase the right to transmit over the subchannels while observing the interference limits set by the PUs and their budget constraints. The utility function of SU is defined as least achievable transmission rate, and that of PU is given by the net profit. We define a market equilibrium in the context of extended Fisher model, and show that the equilibrium is yielded by solving an optimization problem, Eisenberg-Gale convex program.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2513-2533
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• 2018

In cognitive radio technology, the overall efficiency of communications systems can be improved without allocating additional bands by allowing a secondary system to utilize the licensed band when the primary system, which has the right to use the band, does not use it. In this paper, we propose a fast and reliable common channel initialization protocol without any exchange of initialization messages between the cluster head and the member nodes in cognitive ad-hoc networks. In the proposed method, the cluster and member nodes perform channel-based spectrum sensing. After sensing, the cluster head transmits a system activation signal through its available channels with a predetermined angle difference pattern. To detect the cluster head's transmission channels and to join the cluster, each member node implements fast Fourier transform (FFT) and computes autocorrelation for the angle difference sequence of the received signal patterns. This is compared to the predetermined reference angle difference pattern. The join-request and channel-decision procedures are presented in this paper. Performance evaluation of the proposed method is presented in the simulation results.

• Convergence Security Journal
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• v.21 no.1
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• pp.209-219
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• 2021

The problem of congestion in the licensed radio channels spectrum can be solved by Cognitive Radio Networks (CRN). Several algorithms exist to ensure the rendezvous between Secondary Users (SUs), they are increasingly efficient, allowing faster rendezvous under multiple scenarios. In parallel, several jamming algorithms are developed to counter rendezvous which are also improving. The goal in CRN is to ensure the rendezvous by warding such jammers with robust algorithms. In this paper, we classify various jamming techniques and analyze the performance of various well-known rendezvous algorithms under jamming attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1884-1903
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• 2019

Device-to-Device (D2D) communications can provide proximity based services in the future 5G cellular networks. It allows short range communication in a limited area with the advantages of power saving, high data rate and traffic offloading. However, D2D communications may reuse the licensed channels with cellular communications and potentially result in critical interferences to nearby devices. To control the interference and improve network throughput in overlaid D2D cellular networks, a novel channel assignment approach is proposed in this paper. First, we characterize the performance of devices by using Poisson point process model. Then, we convert the throughput maximization problem into an optimal spectrum allocation problem with signal to interference plus noise ratio constraints and solve it, i.e., assigning appropriate fractions of channels to cellular communications and D2D communications. In order to mitigate the interferences between D2D devices, a cluster-based multi-channel assignment algorithm is proposed. The algorithm first cluster D2D communications into clusters to reduce the problem scale. After that, a multi-channel assignment algorithm is proposed to mitigate critical interferences among nearby devices for each D2D cluster individually. The simulation analysis conforms that the proposed algorithm can greatly increase system throughput.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.69-75
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• 2018

Recently, Non-orthogonal multiple access (NOMA) has been focused for the next generation multiple access, which has more spectral efficiency under the limited spectrum bandwidth. Moreover, the spectrum efficiency can be improved by cognitive radio in which the unlicensed secondary users can access the spectrum that is used by the licensed primary user under the limited interference. Hence, we consider the combination of NOMA and cognitive radio, and derive the performance of the cognitive cooperative NOMA system. For the cooperation, a relay is selected among near users, and the selection combining is assumed at a far user. The outage probability of the selected relay and the far user is derived in closed-form, respectively. The provided numerical results are matched well with the Monte Carlo simulation. Numerical results showed that the performance of the relay is affected from the power allocation coefficient, the minimum outage probability is observed at 0.86 of the power allocation coefficient for far user under the given conditions. More than 15 dB of signal-to-noise ratio is required to meet the outage probability of $1{\times}10^{-13}$ for the far user with the frequency acquisition probability of 0.5 compared to that of 1. It shows that the performance of the far user is very sensitive to the acquisition probability of the cognitive relay.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.10
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• pp.299-308
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• 2023

As the spectrum shortage problem has accelerated by the emergence of various services, New Radio-Unlicensed (NR-U) has appeared, allowing users who communicated in licensed bands to communicate in unlicensed bands. However, NR-U network users reduce the performance of Wi-Fi network users who communicate in the same unlicensed band. In this paper, we aim to simultaneously maximize the fairness and throughput of the unlicensed band, where the NR-U network users and the WiFi network users coexist. First, we propose an optimal power allocation scheme based on Monte Carlo Policy Gradient of reinforcement learning to maximize the sum of rates of NR-U networks utilizing rate-splitting multiple access in unlicensed bands. Then, we propose a channel occupancy time division algorithm based on sequential Raiffa bargaining solution of game theory that can simultaneously maximize system throughput and fairness for the coexistence of NR-U and WiFi networks in the same unlicensed band. Simulation results show that the rate splitting multiple access shows better performance than the conventional multiple access technology by comparing the sum-rate when the result value is finally converged under the same transmission power. In addition, we compare the data transfer amount and fairness of NR-U network users, WiFi network users, and total system, and prove that the channel occupancy time division algorithm based on sequential Raiffa bargaining solution of this paper satisfies throughput and fairness at the same time than other algorithms.