• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1471-1488
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• 2018

Interference mitigation is a significant issue in the cognitive heterogeneous networks, this paper studied how to reduce the interference to macrocell users (MU) and improve system throughput. Establish the interference model with imperfect spectrum sensing by analyzing the source of interference complexity. Based on the user topology, the optimize problem was built to maximize the downlink throughput under given interference constraint and the total power constraint. We decompose the resource allocation problem into subcarrier allocation and power allocation. In the subcarrier assignment step, the allocated number of subcarriers satisfies the requirement of the femtocell users (FU).Then, we designed the power allocation algorithm based on the Lagrange multiplier method and the improved water filling method. Simulation results and performance analyses show that the proposed algorithm causes less interference to MU than the algorithm without considering imperfect spectrum sensing, and the system achieves better throughput performance.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2647-2662
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• 2014

This paper proposes an efficient and low complexity power-loading algorithm for MIMO-OFDM downlink based cognitive radio system that maximizes the sum rate of single secondary user (SU) under constraints on the tolerable interference thresholds between secondary user and primary user's frequency bands and the total transmission power. Our suboptimal algorithm is based on the $2^{nd}$ order interference tracking and nulling mechanism to allocate transmission power of the subcarriers among SU's scheme. The performance of our proposed suboptimal scheme is compared with the performance of the classical power loading algorithms, e.g., water filling, $1^{st}$ order interference tracking, nulling, and other suboptimal schemes. Numerical results show that our algorithm has low complexity but obtains a higher channel capacity than that of some previous suboptimal algorithms in some scenarios. We dedicate also that for a given interference threshold, the $2^{nd}$ order interference tracking mechanism has dynamic number of nulling position instead fixed number of nulling position.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.691-708
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• 2010

An important issue of supporting multi-users with diverse quality-of-service (QoS) requirements over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resource while, at the same time, to meet each communication service QoS requirement. In this work, we study the problem of a variety of communication services over multi-media heterogeneous cognitive OFDM system. We first divide the communication services into two parts. Multimedia applications such as broadband voice transmission and real-time video streaming are very delay-sensitive (DS) and need guaranteed throughput. On the other side, services like file transmission and email service are relatively delay tolerant (DT) so varying-rate transmission is acceptable. Then, we formulate the scheduling as a convex optimization problem, and propose low complexity distributed solutions by jointly considering channel assignment, bit allocation, and power allocation. Unlike prior works that do not care computational complexity. Furthermore, we propose the FAASA (Fairness Assured Adaptive Sub-carrier Allocation) algorithm for both DS and DT users, which is a dynamic sub-carrier allocation algorithm in order to maximize throughput while taking into account fairness. We provide extensive simulation results which demonstrate the effectiveness of our proposed schemes.

• Journal of Information Processing Systems
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• v.5 no.3
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• pp.151-158
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• 2009

This paper proposes a utility-based data rate allocation algorithm to provide high-quality mobile video streaming over femtocell networks. We first derive a utility function to calculate the optimal data rates for maximizing the aggregate utilities of all mobile users in the femtocell. The total sum of optimal data rates is limited by the link capacity of the backhaul connections. Furthermore, electromagnetic cross-talk poses a serious problem for the backhaul connections, and its influence passes on to mobile users, as well as causing data rate degradation in the femtocell networks. We also have studied a fixed margin iterative water-filling algorithm to achieve the target data rate of each backhaul connection as a counter-measure to the cross-talk problem. The results of our simulation show that the algorithm is capable of minimizing the transmission power of backhaul connections while guaranteeing a high overall quality of service for all users of the same binder. In particular, it can provide the target data rate required to maximize user satisfaction with the mobile video streaming service over the femtocell networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8A
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• pp.743-751
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• 2010

OFDMA femtocell becomes an effective solution to support indoor high data rate services instead of the macrocell systems. Although the advantage of the femtocell, the co-channel interference between the femocell and the macrocell is the most significant problem that reduces the system performance. Macrocell users who have no permission to access the femtocell suffer from interference of the downlink transmission of femtocell. Therefore, the femtocell should use transmission power as small as possible to reduce interference to macrocell users. In this paper, we define the margin adaptive power allocation problem for the femtocell and propose a heuristic power allocation algorithm to solve the problem. Simulation results show the performance of the proposed algorithm.

• Journal of Communications and Networks
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• v.16 no.5
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• pp.523-533
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• 2014

Orthogonal frequency division multiple access (OFDMA) is a promising technique, which can provide high downlink capacity for the future wireless systems. The total capacity of OFDMA can be maximized by adaptively assigning subchannels to the user with the best gain for that subchannel, with power subsequently distributed by water-filling. In this paper, we propose the use of composite differential evolution (CoDE) algorithm to allocate the subchannels. The CoDE algorithm is population-based where a set of potential solutions evolves to approach a near-optimal solution for the problem under study. CoDE uses three trial vector generation strategies and three control parameter settings. It randomly combines them to generate trial vectors. In CoDE, three trial vectors are generated for each target vector unlike other differential evolution (DE) techniques where only a single trial vector is generated. Then the best one enters the next generation if it is better than its target vector. It is shown that the proposed method obtains higher sum capacities as compared to that obtained by previous works, with comparable computational complexity.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.831-843
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• 2015

This study estimates MODIS-derived evapotranspiration data quality by revised RS-PM algorithm in Seolmacheon test basin. We used latent flux with eddy covariance method to evaluate MODIS-derived spatial evapotranspiration and gap-filled these data by three methods (FAO-PM, MDV and Kalman Filter) and to quantify daily evapotranspiration. Gap-filled daily evapotranspiration data was used to evaluate evapotranspiration computed by revised RS-PM algorithm derived MODIS satellite images. For the water budget analysis, we used soil moisture content that is quantified to average individual soil moisture rate observed by TDR (Time Domain Reflectometry) sensor at soil depth. The soil moisture variation is calculated in consideration from initial to final soil moisture content. According to the result of this study, evapotranspiration computed by revised RS-PM algorithm is very larger than eddy covariance data gap-filled by three methods. Also, water budget characteristics is not closed. We could analysis that MODIS-derived spatial evapotranspiration does not represent actual evapotranspiration in Seolmacheon.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.4
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• pp.8-12
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• 2009

We propose BMPA(balanced multimedia packet allocation) scheme. This scheme considers the issue of optimal sub-carrier allocation in OFDMA multicast system. When RT(real time) packets and NRT(non-real time) packets arrive at the same time, BMPA scheme gives higher weight to RT packets than NRT packets and then, it allocates sub-carriers according to the total weight sum of packets in each user. This process acts as both packet scheduler and sub-carrier allocation. Therefore, each user receives multimedia packets with reliability. With simulation results, it shows that BMPA scheme ensures long-term system throughput and, in average RT packet delay, BMPA scheme greatly outperforms multi-user water-filling algorithm.

• Journal of Communications and Networks
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• v.18 no.6
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• pp.902-912
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• 2016

Recent advances in energy harvesting (EH) technology have motivated the adoption of rechargeable mobile devices for communications. In this paper, we consider a point-to-point (P2P) wireless communication system in which an EH transmitter with a non-ideal rechargeable battery is required to send a given fixed number of bits to the receiver before they expire according to a preset delay constraint. Due to the possible energy loss in the storage process, the harvest-use-and-store (HUS) architecture is adopted. We characterize the properties of the optimal solutions, for additive white Gaussian channels (AWGNs) and then block-fading channels, that maximize the energy efficiency (i.e., battery residual) subject to a given rate requirement. Interestingly, it is shown that the optimal solution has a water-filling interpretation with double thresholds and that both thresholds are monotonic. Based on this, we investigate the optimal double-threshold based allocation policy and devise an algorithm to achieve the solution. Numerical results are provided to validate the theoretical analysis and to compare the optimal solutions with existing schemes.