• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1A
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• pp.72-78
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• 2006

It is impossible to provide full diversity and full rate simultaneously using more than two transmit antennas in transmit diversity system. To do this, simple interference cancellation scheme and transmit power allocation scheme have been proposed, recently. But the former has increased noise power and the latter has increased interference which is induced by other channel in fading channel. In this paper, we propose an adaptive transmit power allocation algorithm to minimize the estimation error in the channel environments which have different fading levels each other and to improve the system performance.

• ETRI Journal
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• v.29 no.4
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• pp.445-451
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• 2007

An adaptive modulation scheme is presented for multiuser orthogonal frequency-division multiplexing systems. The aim of the scheme is to minimize the total transmit power with a constraint on the transmission rate for users, assuming knowledge of the instantaneous channel gains for all users using a combined bit-loading and subcarrier allocation algorithm. The subcarrier allocation algorithm identifies the appropriate assignment of subcarriers to the users, while the bit-loading algorithm determines the number of bits given to each subcarrier. The proposed bit-loading algorithm is derived from the geometric progression of the additional transmission power required by the subcarriers and the arithmetic-geometric means inequality. This algorithm has a simple procedure and low computational complexity. A heuristic approach is also used for the subcarrier allocation algorithm, providing a trade-off between complexity and performance. Numerical results demonstrate that the proposed algorithms provide comparable performance with existing algorithms with low computational cost.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4A
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• pp.316-323
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• 2009

Power allocation of soft frequency reuse(SFR) to increase cell edge user throughput by reducing inter-cell interference is proposed for coordinated cellular systems. SFR is the effective technique to increase cell edge user throughput, however, it costs the degradation of total system throughput. The cost increases when SFR operated in distributed resource controlled systems fails to be fast adaptive in the change of user distribution. The proposed scheme enables coordinated cells to control transmit power adaptively depending on user distribution so that it minimizes the loss of system throughput introduced from SFR while it guarantees enhancement of cell edge user throughput. Through system level simulation considering neighboring two cells, evaluation result for adaptive power allocation is shown compared with static power allocation.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.136-140
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• 2007

In this paper, an adaptive minimum transmit power modulation scheme under constant data rate and fixed bit error rate (BER) for the multiple-input multiple-output (MIMO) system is proposed. It adjusts the modulation order and allocates the transmit power to each spatial sub-channel when meeting the user's requirements at the cost of minimum transmission power. Compared to the other algorithm, it can obtain good performance with lower computational complexity and can be applied to the wireless communication system. Computer simulation results present the efficiency of the proposed scheme. And its performance under different channel condition has been compared with the other algorithm.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.218-220
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• 2004

Orthogonal frequency division multiplexing(OFDM) is one of the most promising technique for next generation wireless broadband communication systems. In this paper, we propose a new bit allocation algorithm in multiuser OFDM. The proposed algorithm is derived from the geometric progression of the additional transmit power of subcarriers and the arithmetic-geometric means inequality. The simulation shows that this algorithm has similar performance to the conventional adaptive bit allocation algorithm and lower computational complexity than the existing algorithms.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.83-84
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• 2007

Multiple-input multiple-output (MIMO) systems can achieve the increasing of performances by using an adaptive power allocation. The related previous work limited the transmit antenna number because orthogonal space-time block codes (OSTBCs) yield full transmit rate only for two transmit antennas. We extend a robust system under imperfect channel estimation for four transmission antennas with maintaining a full transmission rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1889-1910
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• 2017

This paper investigates a protocol so-called Adaptive Harvest Then Transmit (AHTT) for wireless powered communication networks (WPCNs) in multiple-input single-output (MISO) downlink systems, which assists in transmitting signals from a multi-antenna transmitter to a single-antenna receiver. Particularly, the power constrained relay is supplied with power by utilizing radio frequency (RF) signals from the source. In order to take advantage of multiple antennas, two different linear processing schemes, including Maximum Ratio Combining (MRC) and Selection Combination (SC) are studied. The system outage capacity and ergodic capacity are evaluated for performance analysis. Furthermore, the optimal power allocation is also considered. Our numerical and simulation results prove that the implementation of multiple antennas helps boost the energy harvesting capability. Therefore, this paper puts forward a new way to the energy efficiency (EE) enhancement, which contributes to better system performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1095-1104
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• 2008

In multiuser OFDM systems, subcarrier and bit allocation plays an important role for the efficient resource use. However, in multiuser adaptive allocation as a non-linear problem, it is impractical to compute all to get the best solution because of the complexity. We set the goal of minimizing the transmit power while satisfying the BER and minimum bits required to transmit through the highest fitness combination of subcarriers and users. The proposed improved genetic algorithm employs the diversity of adaptive allocation more than existing genetic algorithm. Therefore, from the numerical simulation results, we find that the proposed heuristic algorithm has more performance than the existing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1790-1806
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• 2015

Utility-based routing is a special type of routing approach using a composite utility metric when making routing decisions in ad hoc and sensor networks. Previous studies on the utility-based routing all use fixed retry limit and a very simple distance related energy model, which makes the utility maximization less efficient and the implementation separated from practice. In this paper, we refine the basic utility model by capturing the correlation of the transmit power, the retry limit, the link reliability and the energy cost. A routing algorithm based on the refined utility model with adaptive transmit power and retry limit allocation is proposed. With this algorithm, packets with different priorities will automatically receive utility-optimal delivery. The design of this algorithm is based on the observation that for a given benefit, there exists a utility-maximum route with optimal transmit power and retry limit allocated to intermediate forwarding nodes. Delivery along the utility-optimal route makes a good balance between the energy cost and the reliability according to the value of the packets. Both centralized algorithm and distributed implementations are discussed. Simulations prove the satisfying performance of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1286-1302
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• 2012

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.