• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.178-188
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• 2024

In the near future, it is expected that there will be billions of connected devices using fifth generation (5G) network services. The recently available base stations (BSs) need to mitigate their loads without changing and at the least monetary cost. The available spectrum resources are limited and need to be exploited in an efficient way to meet the ever-increasing demand for services. Device to Device communication (D2D) technology will likely help satisfy the rapidly increasing capacity and also effectively offload traffic from the BS by distributing the transmission between D2D users from one side and the cellular users and the BS from the other side. In this paper, we propose to apply D2D overlay communication with cognitive radio capability in 5G networks to exploit unused spectrum resources taking into account the dynamic spectrum access. The performance metrics; throughput and delay are formulated and analyzed for CSMA-based medium access control (MAC) protocol that utilizes a common control channel for device users to negotiate the data channel and address the contention between those users. Device users can exploit the cognitive radio to access the data channels concurrently in the common interference area. Estimating the achievable throughput and delay in D2D communication in 5G networks is not exploited in previous studies using cognitive radio with CSMA-based MAC protocol to address the contention. From performance analysis, applying cognitive radio capability in D2D communication and allocating a common control channel for device users effectively improve the total aggregated network throughput by more than 60% compared to the individual D2D throughput without adding harmful interference to cellular network users. This approach can also reduce the delay.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.1-11
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• 2024

Cognitive small cell networks, consisting of macro-cells and small cells, are foreseen as a promising candidate solution to address 5G spectrum scarcity. Recently, many technological issues (such as spectrum sensing, spectrum sharing) related to cognitive small cell networks have been studied, but the common control channel (CCC) establishment problem has been ignored. CCC is an indispensable medium for control message exchange that could have a huge significant on transmitter-receiver handshake, channel access negotiation, topology change, and routing information updates, etc. Therefore, establishing CCC in cognitive small cell networks is a challenging problem. In this paper, we propose a potential game theory-based approach for CCC establishment in cognitive radio networks. We design a utility function and demonstrate that it is an exact potential game with a pure Nash equilibrium. To maintain the common control channel list (CCL), we develop a CCC update algorithm. The simulation results demonstrate that the proposed approach has good convergence. On the other hand, it exhibits good delay and overhead of all networks.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.104-109
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• 2016

In this paper, a localization method for multiple robots based on Bayesian inference is proposed when multiple robots adopting multi-RAT (Radio Access Technology) communications exist in cognitive radio networks. Multiple robots are separately defined by primary and secondary users as in conventional mobile communications system. In addition, the heterogeneous spectrum environment is considered in this paper. To improve the performance of localization for multiple robots, a realistic multiple primary user distribution is explained by using the probabilistic graphical model, and then we introduce the Gibbs sampler strategy based on Bayesian inference. In addition, the secondary user selection minimizing the value of GDOP (Geometric Dilution of Precision) is also proposed in order to overcome the limitations of localization accuracy with Gibbs sampling. Via the simulation results, we can show that the proposed localization method based on GDOP enhances the accuracy of localization for multiple robots. Furthermore, it can also be verified from the simulation results that localization performance is significantly improved with increasing number of observation samples when the GDOP is considered.

• Journal of Communications and Networks
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• v.17 no.4
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• pp.406-418
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• 2015

Cognitive radio networks (CRNs) have emerged as a promising solution to the problem of spectrum under utilization and artificial radio spectrum scarcity. The paradigm of dynamic spectrum access allows a secondary network comprising of secondary users (SUs) to coexist with a primary network comprising of licensed primary users (PUs) subject to the condition that SUs do not cause any interference to the primary network. Since it is necessary for SUs to avoid any interference to the primary network, PU activity precludes attempts of SUs to access the licensed spectrum and forces frequent channel switching for SUs. This dynamic nature of CRNs, coupled with the possibility that an SU may not share a common channel with all its neighbors, makes the task of multicast routing especially challenging. In this work, we have proposed a novel multipath on-demand multicast routing protocol for CRNs. The approach of multipath routing, although commonly used in unicast routing, has not been explored for multicasting earlier. Motivated by the fact that CRNs have highly dynamic conditions, whose parameters are often unknown, the multicast routing problem is modeled in the reinforcement learning based framework of learning automata. Simulation results demonstrate that the approach of multipath multicasting is feasible, with our proposed protocol showing a superior performance to a baseline state-of-the-art CRN multicasting protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3711-3730
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• 2014

Cognitive radio networks (CRNs) have emerged as a promising solution to enhance spectrum utilization by using unused or less used spectrum in radio environments. The basic idea of CRNs is to allow secondary users (SUs) access to licensed spectrum, under the condition that the interference perceived by the primary users (PUs) is minimal. In CRNs, the channel availability is uncertainty due to the existence of PUs, resulting in intermittent communication. Transmission control protocol (TCP) performance may significantly degrade in such conditions. To address the challenges, some transport protocols have been proposed for reliable transmission in CRNs. In this paper we survey the state-of-the-art transport protocols for CRNs. We firstly highlight the unique aspects of CRNs, and describe the challenges of transport protocols in terms of PU behavior, spectrum sensing, spectrum changing and TCP mechanism itself over CRNs. Then, we provide a summary and comparison of existing transport protocols for CRNs. Finally, we discuss several open issues and research challenges. To the best of our knowledge, our work is the first survey on transport protocols for CRNs.

• 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.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.193-201
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• 2014

In cognitive radio networks, the packet transmissions of the secondary users (SUs) can be interrupted randomly by the primary users (PUs). That is to say, the PU packets have preemptive priority over the SU packets. In order to enhance the quality of service (QoS) for the SUs, we propose a spectrum access strategy with an ${\alpha}$-Retry policy. A buffer is deployed for the SU packets. An interrupted SU packet will return to the buffer with probability ${\alpha}$ for later retrial, or leave the system with probability (1-${\alpha}$). For mathematical analysis, we build a preemptive priority queue and model the spectrum access strategy with an ${\alpha}$-Retry policy as a two-dimensional discrete-time Markov chain (DTMC).We give the transition probability matrix of the Markov chain and obtain the steady-state distribution. Accordingly, we derive the formulas for the blocked rate, the forced dropping rate, the throughput and the average delay of the SU packets. With numerical results, we show the influence of the retrial probability for the strategy proposed in this paper on different performance measures. Finally, based on the trade-off between different performance measures, we construct a cost function and optimize the retrial probabilities with respect to different system parameters by employing an iterative algorithm.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.183-192
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• 2014

This paper proposes a payment-based power control scheme using non-cooperative game with a novel pricing function in cognitive radio networks (CRNs). The proposed algorithm considers the fairness of power control among second users (SUs) where the value of per SU' signal to noise ratio (SINR) or distance between SU and SU station is used as reference for punishment price setting. Due to the effect of uncertainty fading environment, the system is unable to get the link gain coefficient to control SUs' transmission power accurately, so the quality of service (QoS) requirements of SUs may not be guaranteed, and the existence of Nash equilibrium (NE) is not ensured. Therefore, an alternative iterative scheme with sliding model is presented for the non-cooperative power control game algorithm. Simulation results show that the pricing policy using SUs' SINR as price punishment reference can improve total throughput, ensure fairness and reduce total transmission power in CRNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.18-34
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• 2014

It is widely believed that cognitive radio (CR) networks have an opportunistic nature and therefore can only support best-effort traffics without quality-of-service (QoS) guarantees. In this paper, we propose a centralized CR network that adopts interference averaging techniques to support QoS guaranteed traffics under interference outage constraints. In such a CR network, a CR user adaptively adjusts its transmit power to compensate for the channel loss, thereby keeping the receive signal power at the CR base station (BS) at a constant level. The closed-form system capacity of such a CR network is analyzed and derived for a single cell with one CR BS and multiple CR users, taking into account various key factors such as interference outage constraints, channel fading, cell radius, and locations of primary users. The accuracy of the theoretical results is validated by Monte Carlo simulations. Numerical and simulation results show promising capacity potential for deploying QoS-guaranteed CR networks in frequency bands with fixed primary receivers. Our work can provide theoretical guidelines for the strategic planning of centralized CR networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3810-3830
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• 2015

In this paper, we investigate the differential game theoretic approach for distributed dynamic cooperative power control in cognitive radio ad hoc networks (CRANETs). First, a payoff function is defined by taking into consideration the tradeoff between the stock of accumulated power interference to the primary networks and the dynamic regulation of the transmit power of secondary users (SUs). Specifically, the payoff function not only reflects the tradeoff between the requirement for quickly finding the stable available spectrum opportunities and the need for better channel conditions, but also reveals the impact of the differentiated types of data traffic on the demand of transmission quality. Then the dynamic power control problem is modeled as a differential game model. Moreover, we convert the differential game model into a dynamic programming problem to obtain a set of optimal strategies of SUs under the condition of the grand coalition. A distributed dynamic cooperative power control algorithm is developed to dynamically adjust the transmit power of SUs under grand coalition. Finally, numerical results are presented to demonstrate the effectiveness of the proposed algorithm for efficient power control in CRANETs.