• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.185-193
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• 2009

This paper presents a methodology for photovoltaic (PV) system allocation in distribution systems using a discrete particle swarm optimization (DPSO). The PV allocation problem is in the category of mixed integer nonlinear programming and its formulation may include multi-valued dis-crete variables. Thus, the PSO requires a scheme to deal with multi-valued discrete variables. This paper introduces a novel multi-level quantization scheme using a sigmoid function for discrete particle swarm optimization. The technique is employed to a standard PSO architecture; the same velocity update equation as in continuous versions of PSO is used but the particle's positions are updated in an alternative manner. The set of multi-level quantization is defined as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming a particle's position into discrete values. A comparison with a genetic algorithm (GA) is performed to verify the quality of the solutions obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7C
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• pp.680-690
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• 2006

In this paper, we present a bit allocation scheme based on grouped sub-channels for MIMO-OFDM (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) systems using V-BLAST (Vertical-Bell laboratories LAyered Space-Time) detector. A fully adaptive modulation and coding scheme may provide optimal performance in the MIMO-OFDM systems, however it requires excessive feedback information. Instead, SBA (Simplified Bit Allocation) scheme for reduction of feedback overhead, which applies the same modulation and coding to all the good sub-channels, may be considered. The proposed scheme in this paper named SBA-GS (Simplified Bit Allocation based on Grouped Sub-channels) groups sub-channels and assigns the same modulation and coding to the set of selected sub-channel groups. Simulation results show that the proposed scheme achieves comparable bit error rate performance of the conventional SBA scheme, while significantly reducing the feedback overhead in multipath channels with small delay spreads.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.924-944
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• 2014

This paper investigates the power allocation and outage performance of MIMO full-duplex relaying (MFDR), based on orthogonal space-time block codes (OSTBC), in cognitive radio systems. OSTBC transmission is used as a simple means to achieve multi-antenna diversity gain. Cognitive MFDR systems not only have the advantage of increasing spectral efficiency through spectrum sharing, but they can also extend coverage through the use of relays. In cognitive MFDR systems, the primary user experiences interference from the secondary source and relay simultaneously, owing to full duplexing. It is therefore necessary to optimize the transmission powers at the secondary source and relay. In this paper, we propose an optimal power allocation (OPA) scheme based on minimizing the outage probability in cognitive MFDR systems. We also analyse the outage probability of the secondary user in noise-limited and interference-limited environments in Nakagami-m fading channels. Simulation results show that the proposed schemes achieve performance improvements in terms of reducing outage probability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.288-307
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• 2013

This paper formulates resource allocation for decode-and-forward (DF) relay assisted multi-cell orthogonal frequency division multiple (OFDM) networks as an optimization problem taking into account of inter-cell interference and users fairness. To maximize the transmit rate of system we propose a joint interference coordination, subcarrier and power allocation algorithm. To reduce the complexity, this semi-distributed algorithm divides the primal optimization into three sub-optimization problems, which transforms the mixed binary nonlinear programming problem (BNLP) into standard convex optimization problems. The first layer optimization problem is used to get the optimal subcarrier distribution index. The second is to solve the problem that how to allocate power optimally in a certain subcarrier distribution order. Based on the concept of equivalent channel gain (ECG) we transform the max-min function into standard closed expression. Subsequently, with the aid of dual decomposition, water-filling theorem and iterative power allocation algorithm the optimal solution of the original problem can be got with acceptable complexity. The third sub-problem considers dynamic co-channel interference caused by adjacent cells and redistributes resources to achieve the goal of maximizing system throughput. Finally, simulation results are provided to corroborate the proposed algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.4
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• pp.349-357
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• 2005

The Adaptive Multi-Rate (AMR) speech codec is the mandatory for voice service in WCDMA systems. The AMR codec can be used efficiently to provide a balanced trade-off between the capacity and quality of voice by adjusting various service rates. In this paper, three ways of AMR mode allocation schemes on the downlink in WCDMA system are evaluated. To evaluate users satisfaction efficiently, new system performance measure and analytic models are proposed. The proposed analytic models can be applied to obtain optimal mode allocation ways while considering the system capacity and quality of voice. In numerical examples, the ways of finding optimal parameters are illustrated for the given traffic loads and the performances of three mode allocation schemes are compared.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.7
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• pp.571-579
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• 2013

This paper proposes an energy-efficient mode selection and power allocation scheme in device-to-device (D2D) communication system as an underlay coexistence with cellular networks. We analyze the energy efficiency which is defined as the summation of the energy efficiencies for all devices. The proposed scheme consists of two steps. First, we calculate the transmission power maximizing the energy efficiency for all possible modes of each device. Although the proposed power cannot maximize the system capacity, we prove that the proposed transmission power is the optimal power which maximizes the energy efficiency. In the second step, we select a mode which has the maximal energy efficiency among all possible mode combinations of the devices. Then we can jointly obtain the transmission power and the mode which can maximize the energy efficiency. The proposed scheme has the optimal performance with respect to the energy efficiency and outperforms the conventional schemes.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.95-107
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• 2012

Network coding was proposed to increase the achievable throughput of multicast in a network. Recently, combining network coding into user cooperation has attracted research attention. For cooperative transmission schemes with network coding, users combine their own and their partners messages by network coding. In previous works, it was shown that adaptive DF with network coding can achieve diversity gain and additional throughput gain. In this paper, to improve performance of conventional protocols and maximize advantage of using network coding, we propose a new network coding based user cooperation scheme which uses adaptively amplify-and-forward and decode-and-forward according to interuser channel status. We derive outage probability bound of proposed scheme and prove that it has full diversity order in the high SNR regime. Moreover, based on the outage bound, we compute optimal power allocation for the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1986-1993
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• 2015

We investigate the optimal resource and power allocation for device-to-device (D2D) communications in a multicell environment. When D2D links reuse the cellular radio resources, each D2D user will interfere with a cellular link and other D2D links, in its own cell as well as in adjacent cells. Under such situation, we propose a coordinated resource allocation scheme that can handle the intercell interferences as well as the intracell interference. For a given resource allocation, we also formulate a power optimization problem and present an algorithm for finding the optimal solution. The resource and power allocation algorithms are designed to maximize the achievable rate of the D2D link, while limiting the generated interference to the cellular link. The performance of the proposed algorithms is evaluated through simulations in a multicell environment. Numerical results are presented to verify the coordination gain in the resource and power allocation.