• 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.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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1255-1261
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• 2016

Recently, the energy harvesting technology in which energy is collected from the wireless signal which is transmitted by mobile communication devices, has been considered as a novel way to improve the life time of wireless sensors by mitigating the lack of power supply problem. In this paper, we consider the optimal sensing time and power allocation problem for cognitive radio systems, where the energy efficiency of secondary user is maximized while the constraint are satisfied, using the optimization technique. Based on the derived optimal solutions, we also have proposed an iterative resource allocation algorithm in which the optimal power and sensing time allocation can be found without excessive computations. The simulation results confirm that the proposed scheme achieves the optimal performance and it outperforms the conventional resource allocation schemes in terms of energy efficiency while the constraints are guaranteed to be satisfied.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4748-4765
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• 2016

We consider a virtualized cognitive radio (CR) network, where multiple virtual network operators (VNOs) who own different virtual cognitive base stations (VCBSs) share the same physical CBS (PCBS) which is owned by an infrastructure provider (InP), sharing the spectrum with the primary user (PU). The uplink scenario is considered where the secondary users (SUs) transmit to the VCBSs. The PU is protected by constraining the interference power from the SUs. Such constraint is applied by the InP through pricing the interference. A Stackelberg game is formulated to jointly maximize the revenue of the InP and the individual utilities of the VNOs, and then the Stackelberg equilibrium is investigated. Specifically, the optimal interference price and channel allocation for the VNOs to maximize the revenue of the InP and the optimal power allocation for the SUs to maximize the individual utilities of the VNOs are derived. In addition, a low‐complexity ±‐optimal solution is also proposed for obtaining the interference price and channel allocation for the VNOs. Simulations are provided to verify the proposed strategies. It is shown that the proposed strategies are effective in resource allocation and the ±‐optimal strategy achieves practically the same performance as the optimal strategy can achieve. It is also shown that the InP will not benefit from a large interference power limit, and selecting VNOs with higher unit rate utility gain to share the resources of the InP is beneficial to both the InP and the VNOs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1837-1860
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• 2020

We propose a general framework for studying resource allocation problem and the tradeoff between spectral efficiency (SE) and energy efficiency (EE) for downlink traffic in power domain-non-orthogonal multiple access (PD-NOMA) and device to device (D2D) based heterogeneous cloud radio access networks (H-CRANs) under imperfect channel state information (CSI). The aim is jointly optimize radio remote head (RRH) selection, spectrum allocation and power control, which is formulated as a multi-objective optimization (MOO) problem that can be solved with weighted Tchebycheff method. We propose a low-complexity algorithm to solve user association, spectrum allocation and power coordination separately. We first compute the CSI for RRHs. Then we study allocating the cell users (CUs) and D2D groups to different subchannels by constructing a bipartite graph and Hungrarian algorithm. To solve the power control and EE-SE tradeoff problems, we decompose the target function into two subproblems. Then, we utilize successive convex program approach to lower the computational complexity. Moreover, we use Lagrangian method and KKT conditions to find the global optimum with low complexity, and get a fast convergence by subgradient method. Numerical simulation results demonstrate that by using PD-NOMA technique and H-CRAN with D2D communications, the system gets good EE-SE tradeoff performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.8
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• pp.1913-1925
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• 2012

In order to efficiently utilize limited radio resources, resource allocation schemes in OFDMA-based wireless networks have gained intensive attention recently. Instead of improving the throughput performance, the utility is adopted as the metric for resource allocation, which provides reasonable methods to build up the relationship between user experience and various quality-of-service (QoS) metrics. After formulating the optimization problem by using a weighted bipartite graph, a modified bipartite matching method is proposed to find a suboptimal solution for the resource allocation problem in OFDMA-based wireless systems with feasible computational complexity. Finally, simulation results are presented to validate the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1638-1653
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• 2014

A sequential optimization algorithm (SOA) for resource allocation in a cyclic-prefixed single-carrier cognitive relay system is proposed in this study. Both subcarrier pairing (SP) and power allocation are performed subject to a primary user interference constraint to minimize the mean squared error of frequency-domain equalization at the secondary destination receiver. Under uniform power allocation at the secondary source and optimal power allocation at the secondary relay, the ordered SP is proven to be asymptotically optimal in maximizing the matched filter bound on the signal-to-interference-plus-noise ratio. SOA implements the ordered SP before power allocation optimization by decoupling the ordered SP from the power allocation. Simulation results show that SOA can optimize resource allocation efficiently by significantly reducing complexity.

• ETRI Journal
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• v.44 no.4
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• pp.531-542
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• 2022

With the increasing demand for unlicensed spectrum, several regulators have been opening up the 6-GHz band for unlicensed use while ensuring compliance with the technical requirement to avoid harmful interference in the existing primary services (PSs). In this paper, we present two methodologies, a channel-based method and a frequency-based method, which are applicable to a frequency coordination system that calculates the permissible transmit power in the channels or frequencies available to a secondary service (SS). In addition, we have demonstrated that the available transmit power of an SS can be maximized by adjusting the power allocation of the assigned resource units under the condition that the channel of the SS is partially overlapped with that of the PS. Based on the analysis results, it is suggested that it would be better to utilize the two methods selectively according to the operating channel conditions of the PS and the SS.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.5
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• pp.103-108
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• 2016

In this paper, we propose a resource allocation scheme that guarantees transmission rate for each mobile stations by mitigating interference between a base station-to-mobile station link and a relay station-to-mobile station link. Specifically, we dynamically adjust the boundary between access zone and relay zone using signal to interference plus noise ratio. Moreover, we cluster the mobile stations under sever interference and manage the channel quality of these mobile stations by allocating additional radio resource. Our simulation results show that the proposed scheme can improve the efficiency of radio resources and ensure fairness among mobile stations.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.256-259
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• 2007

Multicast and Broadcast Service (MBS) provides flexible and efficient transmission of the same information to multiple users using shared radio resources on WiBro network. The advantage of this service is to achieve the most efficient use of radio and network resources as well as to lessen sender's processing load when sending the same information to multiple users. Though radio resources are saved since a multicast or broadcast transport connection is associated with a service flow, it is hard to change MBS service channel dynamically. In this paper, we propose a Radio Resource Management System (RRMS) for supporting dynamic scheduling of MBS service channels. Results show that our proposed scheme using Radio Resource Allocation Table (RRAT) can efficiently support MBS services by providing dynamic schedule for MBS service channels.