• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권5호
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• pp.1514-1531
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• 2014

Femtocell provides better coverage and higher spectrum efficiency in areas rarely covered by macrocells. However, serious two-tier interference emerging from randomly deploying femtocells may create dead zones where the service is unavailable for macro-users. In this paper, we present adopting cognitive radio spectrum overlay to avoid intra-tier interference and incorporating spectrum underlay and overlay to coordinate cross-tier interference. It is a novel centralized control strategy appropriate for both uplink and downlink transmission. We introduce the application of proper spectrum sharing strategy plus optimal power allocation to address the issue of OFDM-based femtocells interference-limited downlink transmission, along with, a low-complexity suboptimal solution proposed. Simulation results illustrate the proposed optimal scheme achieves the highest transmission rate on successfully avoiding two-tier interference, and outperforms the traditional spectrum underlay or spectrum overlay, via maximizing the opportunity to transmit. Moreover, the strength of our proposed schemes is further demonstrated by comparison with previous classic power allocation methods, in terms of transmission rate, computational complexity and signal peak-to-average power ratio.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권12호
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• pp.5191-5211
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• 2016

It is essential to satisfy class-specific QoS constraints to provide broadband services for new generation networks. The present study proposes a QoS-driven multicast scheme for wireless networks in which the transmission rate and end-to-end delay are assumed to be bounded during a multiple multicast session. A distributed algorithm was used to identify a cost-efficient sub-graph between the source and destination which can satisfy QoS constraints of a multicast session. The model was then modified as to be applied for wireless networks in which satisfying interference constraints is the main challenge. A discrete power control scheme was also applied for the QoS-aware multicast model to accommodate the effect of transmission power level based on link capacity requirements. We also proposed random power allocation (RPA) and gradient power allocation (GPA) algorithms to efficient resource distribution each of which has different time complexity and optimality levels. Experimental results confirm that the proposed power allocation techniques decrease the number of unavailable links between intermediate nodes in the sub-graph and considerably increase the chance of finding an optimal solution.

• Journal of Communications and Networks
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• 제13권4호
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• pp.360-366
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• 2011

In this paper, we investigate the problem of power allocation in a heterogeneous network that is composed of a pair of cognitive users (CUs) and an infrastructure-based primary network. Since CUs have only limited effective spectrum-sensing ability and primary users (PUs) are not active all the time in all locations and licensed bands, we set up a new multi-area model to characterize the heterogeneous network. A novel combined interference-avoidance policy corresponding to different PU-appearance situations is introduced to protect the primary network from unacceptable disturbance and to increase the spectrum secondary-reuse efficiency. We use dual decomposition to transform the original power allocation problem into a two-layer optimization problem. We propose a low-complexity joint power-optimizing method to maximize the transmission rate between CUs, taking into account both the individual power-transmission constraints and the combined interference power constraint of the PUs. Numerical results show that for various values of the system parameters, the proposed joint optimization method with combined PU protection is significantly better than the opportunistic spectrum access mode and other heuristic approaches.

• IEIE Transactions on Smart Processing and Computing
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• 제2권3호
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• pp.160-167
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• 2013

Resource allocation based on quantized feedback plays a critical role in wireless mesh networks with a time division multiple access (TDMA) physical layer. In this study, a resource allocation problem was formulated based on quantized feedback for TDMA wireless mesh networks that minimize the total transmission power. Three steps were taken to solve the optimization problem. In the first step, the codebook of the power, rate and equivalent channel quantization threshold was designed. In the second step, the timeslot allocation criterion was deduced using the primal-dual method. In the third step, a resource allocation scheme was developed based on quantized feedback using the stochastic optimization tool. The simulation results show that the proposed scheme not only reduces the total transmission power, but also has the advantage of quantized feedback.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.438-440
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• 2002

In deregulated power market, transmission pricing methodology should maintain non-discrimination amongst all participants while ensure that TRANSCOs recover their revenue requirements. The proposed transmission pricing methodology for Korea needs cost allocation ratios, such as allocation ratio of physical transport to network security and that of generators to loads. In this paper, we studied the nodal transmission price determined by the cost allocation factors and its influence on GENCOs and DISTCOs.

• 한국통신학회논문지
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• 제33권12A호
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• pp.1138-1146
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• 2008

This paper considers 2-hop wireless cooperative communications networks with fixed decode-and-forward relays. Specifically, we first derive the closed-form BER expression for theoretically evaluating the end-to-end performance of these networks. Then, based on this expression and long-tenn fading statistics, we propose a power allocation method for source and relay. Such a method brings about multiple advantages in tenn of spectral efficiency and implementation complexity over other power allocation methods based on instantaneous fading statistics. A variety of numerical results reveal that the cooperative communications scheme with the proposed power allocation significantly outperforms that with the equal power allocation and the direct transmission scheme for any position of the relay subject to the same total transmit power constraint.

• Journal of Communications and Networks
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• 제18권3호
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• pp.375-386
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• 2016

Most existing studies on broadcast services in orthogonal frequency division multiplexing (OFDM) systems have focused on how to allocate the transmission power to the subcarriers. However, because a broadcasting system must guarantee quality of service to all users, the performance of the broadcast service dominantly depends on the channel state of the user who has the lowest received signal-to-noise ratio among users. To reduce the effect of the worst user on the system performance, we propose a joint delivery scheme of unicast and broadcast transmissions in OFDM systems with broadcast and unicast best-effort users. In the proposed joint delivery scheme, the BS delivers the broadcast information using both the broadcast and unicast subcarriers at the same time in order to improve the performance of the broadcast service. The object of the proposed scheme is to minimize the outage probability of the broadcast service while maximizing the sum-rate of best-effort users. For the proposed joint delivery scheme, we develop an adaptive power and subcarrier allocation algorithm under the constraint of total transmission power. This paper shows that the optimal power allocation over each subcarrier in the proposed scheme has a multi-level water filling form. Because the power allocation and the subcarrier assignment problems should be jointly solved, we develop an iterative algorithm to find the optimal solution. Numerical results show that the proposed joint delivery scheme with adaptive power and subcarrier allocation outperforms the conventional scheme in terms of the outage probability of the broadcast service and the sum-rate of best-effort users.

• 한국통신학회논문지
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• 제35권8A호
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• pp.743-751
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• 2010

OFDMA 초소형 기지국은 기존의 대형 기지국을 대신하여 실내에서의 고속 데이터 통신을 지원하기 위해 개발된 기술이지만 아직 실용화를 위해 해결해야할 여러 문제를 가지고 있다. 특히 초소형 기지국이 대형 기지국과 같은 주파수 대역을 사용할 경우 발생하는 셀간 간섭 문제는 시스템의 성능을 저하시키는 주요 원인이 된다. 초소형 기지국에 대한 사용 권한이 없는 사용자는 초소형 기지국의 서비스 영역 내에서도 대형 기지국과 통신을 수행하여야 하며 이때 하향링크에서 초소형 기지국의 전송 신호는 대형 기지국 사용자에게 간섭으로 작용하게 된다. 따라서 초소형 기지국의 전송 전력을 최소화하여 대형 기지국 사용자에게 미치는 간섭을 제어할 필요가 있다. 본 논문에서는 초소형 기지국의 전력 할당을 위한 margin adaptive 문제를 정의하고 이를 해결하기 위한 휴리스틱기법을 제안한다. 또한 모의실험을 통해 제안한 기법의 성능을 검증한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권6호
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• pp.1379-1397
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• 2013

We consider a system where a licensed radio spectrum is shared by multiple primary users(PUs) and secondary users(SUs). As the spectrum of interest is licensed to primary network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to PUs. For this system, we study the joint beamforming and power allocation problem via game theory in this paper. The problem is formulated as a non-cooperative beamforming and power allocation game, subject to the interference constraints of PUs as well as the peak transmission power constraints of SUs. We design a joint beamforming and power allocation algorithm for maximizing the total throughput of SUs, which is implemented by alternating iteration of minimum mean square error based decision feedback beamforming and a best response based iterative power allocation algorithm. Simulation results show that the algorithm has better performance than an existing algorithm and can converge to a locally optimal sum utility.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.226-238
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• 2024

Recently, multi-access edge computing (MEC) has emerged as a promising technology to alleviate the computing burden of vehicular terminals and efficiently facilitate vehicular applications. The vehicle can improve the quality of experience of applications by offloading their tasks to MEC servers. However, channel conditions are time-varying due to channel interference among vehicles, and path loss is time-varying due to the mobility of vehicles. The task arrival of vehicles is also stochastic. Therefore, it is difficult to determine an optimal offloading with resource allocation decision in the dynamic MEC system because offloading is affected by wireless data transmission. In this paper, we study computation offloading with resource allocation in the dynamic MEC system. The objective is to minimize power consumption and maximize throughput while meeting the delay constraints of tasks. Therefore, it allocates resources for local execution and transmission power for offloading. We define the problem as a Markov decision process, and propose an offloading method using deep reinforcement learning named deep deterministic policy gradient. Simulation shows that, compared with existing methods, the proposed method outperforms in terms of throughput and satisfaction of delay constraints.