• Journal of Communications and Networks
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• v.11 no.4
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• pp.368-374
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• 2009

This paper focuses on a distributed multiple spectrum pricing scheme to maximize system capacity in next generation multiaccess systems, where multimode user equipments (MUEs) can connect simultaneously to multiple base stations (BSs) with multiple radio access technologies (RATs). The multi-price based scheme provides a distributed decision making for an optimal solution where radio resource allocations are determined by each MUE, unlike most centralized mechanisms where BS controls the whole radio resource. By the proposed optimal solution, MUEs can decide their share of spectrum bands and power allocation according to the spectrum price of each RAT, and at the same time the multiaccess system can achieve maximized total throughput. Numerical analysis shows that the proposed scheme achieves the maximal capacity by distributed resource allocation for the multiaccess system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1057-1073
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• 2015

In this paper, we consider cooperative D2D communications in cellular networks. More precisely, a cellular user leases part of its spectrum to facilitate the D2D communication with a goal of improving the energy efficiency of a D2D pair. However the D2D pair is untrusted to the cellular user, such resource sharing may result in the information of this cellular user unsecured. In order to motivate the cellular user's generosity, this D2D pair needs to help the cellular user maintain a target secrecy rate. To address this issue, we formulate a joint spectrum and power allocation problem to maximize the energy efficiency of the D2D communication while guaranteeing the physical layer security of the cellular user. Then, a theorem is proved to indicate the best resource allocation strategy, and accordingly, an algorithm is proposed to find the best solution to this resource allocation problem. Numerical results are finally presented to verify the validity and effectiveness of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1533-1546
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• 2013

Wireless multicast is considered as an effective transmission mode for the future mobile social contact services supported by Long Time Evolution (LTE). Though wireless multicast has an excellent resource efficiency, its performance suffers deterioration from the channel condition and wireless resource availability. Cognitive Radio (CR) and Device to Device (D2D) are two solutions to provide potential resource. However, resource allocation for cognitive wireless multicast based on D2D is still a great challenge for LTE social networks. In this paper, a joint sub-carriers and power allocation model based on D2D for general cognitive radio multicast (CR-D2D-MC) is proposed for Orthogonal Frequency-Division Multiplexing (OFDM) LTE systems. By opportunistically accessing the licensed spectrum, the maximized capacity for multiple cognitive multicast groups is achieved with the condition of the general scenario of imperfect spectrum sensing, the constrains of interference to primary users (PUs) and an upper-bound power of secondary users (SUs) acting as multicast source nodes. Furthermore, the fairness for multicast groups or unicast terminals is guaranteed by setting a lower-bound number of the subcarriers allocated to cognitive multicast groups. Lagrange duality algorithm is adopted to obtain the optimal solution to the proposed CR-D2D-MC model. The simulation results show that the proposed algorithm improves the performance of cognitive multicast groups and achieves a good balance between capacity and fairness.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.1-10
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• 2021

In recent decades, the heterogeneous and dynamic behavior of Internet traffic has placed new demands on the adaptive resource allocation of the optical network infrastructure. However, the advent of multifiber elastic optical networks has led to a higher degree of spectrum fragmentation than conventional flexible grid networks due to the dynamic and random establishment and removal of optical connections. In this paper, we propose heuristic routing and dynamic slot allocation algorithms to minimize spectrum fragmentation and reduce the probability of blocking future connection requests by considering the power consumption in elastic multifiber elastic optical networks.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.495-500
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• 2012

A standard paradigm for the allocation of wireless resources in communication demands symmetry, whereby all users are assumed to be on equal footing and hence get equal shares of communication capabilities. However, there are situations in which "prime users" should be given higher priority, as for example in the transmission of emergency messages. In this paper, we examine a prioritization policy that can be implemented at the physical layer. In particular, we evaluate the performance of a prioritized transmission scheme based on spectrum pooling and on the assignment of higher signal-to-noise ratio channels to higher-priority users. This performance is compared to that of unprioritized (or "symmetric") schemes, and the impact of prioritization on the unprioritized users is discussed.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1468-1474
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• 2015

Efficient spectrum sharing is an important issue in Device-to-Device (D2D) communications underlaying cellular networks as it can mitigate the interference to cellular users and improve the performance of the systems. In this paper, we formulate the radio resource allocation in D2D communications as a mixed nonlinear integer programing. We show the formulated problem is NP-hard and thus a polynomial time algorithm to solve is not possible. Since such a problem is very hard to obtain the optimal solution within a short running time, we instead propose a fast heuristic suboptimal algorithm to mitigate the interference caused to cellular users and improve the performance of the systems. Simulation results are provided to evaluate the performance of the proposed algorithm.

• ETRI Journal
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• v.38 no.6
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• pp.1153-1162
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• 2016

This paper addresses the resource allocation (RA) problem in multi-cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered-such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP-hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub-gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.112-122
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• 2016

Cognitive radio (CR) is considered an attractive technology to deal with the spectrum scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity because data are transmitted by multiple RANs (radio access networks) concurrently. Thus, multi-RAT embedded in a cognitive radio network (CRN) is a promising paradigm for developing spectrum efficiency and network capacity in future wireless networks. In this study, we consider a new CRN model in which the primary user networks consist of heterogeneous primary users (PUs). Specifically, we focus on the energy-efficient resource allocation (EERA) problem for CR users with a special location coverage overlapping region in which heterogeneous PUs operate simultaneously via multi-RAT. We propose a two-tier crossover genetic algorithm-based search scheme to obtain an optimal solution in terms of the power and bandwidth. In addition, we introduce a radio environment map to manage the resource allocation and network synchronization. The simulation results show the proposed algorithm is stable and has faster convergence. Our proposal can significantly increase the energy efficiency.

• Journal of Satellite, Information and Communications
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• v.4 no.2
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• pp.5-11
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• 2009

In this paper, we propose our design of adaptive resource allocation in the cognitive radio network assisted by satellite to improve the performance of Cognitive Radio user. Most of today’s telecommunication network operates in a fixed, licensed frequency band using a specific spectrum access network. However, the spectrum is not always used all the time, all the band. It causes the inefficiency in the spectrum usage. Thus, cognitive radio network is proposed to solve these spectrum inefficiency problems. The cognitive radio users (secondary users) are coexistent with primary users (PUs) who are licensed. That cognitive radio network is considered as lower priority comparing with primary user. So, the operation of the cognitive radio network is limited to interference constraints. Especially, when the number of secondary users increases, CCI among SUs will increase as well as interference to PU. That motivates our objective to improve the performance even if cognitive radio users increase. To solve this problem, we suggest an adaptive resource allocation scheme to improve the performance of cognitive radio network assisted by satellite. Through this algorithm, we can improve the cognitive radio network performance. And the simulation results confirm the effectiveness of our proposed algorithm.