• Journal of Communications and Networks
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• v.6 no.3
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• pp.226-234
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• 2004

This work presents a deterministic channel that rules according to inverse a power propagation law. The proposed channel model allows us to derive the lower bound and upper bound of packet's capture probability in Rayleigh fading and shadowing cellular mobile system. According to these capture probabilities, we analyze the system performance in the case of finite stations and finite communicated coverage of a base station. We also adopted a dynamic backoff window size to discuss the robustness of IEEE 802.11 draft standard. Some suggestions and conclusions from numerical results are given to establish the more strong CSMA/CA protocol.

• ETRI Journal
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• v.37 no.5
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• pp.845-855
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• 2015

To enable the coexistence of Licensed Assisted Access (LAA) and Wi-Fi in 5 GHz unlicensed bands, a new channel access mechanism is proposed. Accounting for the fairness between LAA and Wi-Fi, the proposed mechanism finds the optimal transmission time ratio by adaptively adjusting the transmission durations for LAA and Wi-Fi. In addition, we propose a new analytical model for the distributed coordination function of IEEE 802.11 through some modifications of conventional analytical models for saturation and non-saturation loads. By computing the activity ratio of Wi-Fi, the proposed analytical model is able to control the time ratio between LAA and Wi-Fi, which is required for practical implementation of the proposed access mechanism. Through numerical simulations, the proposed channel access mechanism is compared with conventional methods in terms of throughput and utility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1208-1220
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• 1996

In this paper, the performance of a Carrier Sense Multiple Access/Collision avoidance (CSMA/CA) protocol using stop-and-Wait automatic Repeat reQuest, which is adapted as a draft standard in IEEE 802.11, is analyzed using a mathematical method based on a renewal theory, and simulation checks are performed, which confirm the goodness of our anlysis. In order to anlayze of CSMA/CA, we model that network is composed of finite populationand channel is slotted. And, we consider the CSMA/CA protocol as a hybrid protocol of 1-persistent CSMA and p-persistent CSMA protocol. As resuls of analysis, we have found that the throughput is degraded and packet delay is increased as the number of stations, Acknowledgement (ACK) length and Distributed coordination function Inter Frame Space (DIFS) length are increased.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.13-20
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• 2022

IEEE 802.11ay Wi-Fi is the next generation wireless technology and operates in mmWave band. It supports the MU-MIMO (Multiple User Multiple Input Multiple Output) transmission in which an AP (Access Point) can transmit multiple data streams simultaneously to multiple STAs (Stations). To this end, the AP should perform MU-MIMO beamforming training with the STAs. For efficient MU-MIMO beamforming training, it is important for the AP to estimate signal strength measured at each STA at which multiple beams are used simultaneously. Therefore, in the paper, we propose a deep learning-based link quality estimation scheme. Our proposed scheme estimates the signal strength with high accuracy by utilizing a deep learning model pre-trained for a certain indoor or outdoor propagation scenario. Specifically, to estimate the signal strength of the multiple concurrent beams, our scheme uses the signal strengths of the respective single beams, which can be obtained without additional signaling overhead, as the input of the deep learning model. For performance evaluation, we utilized a Q-D (Quasi-Deterministic) Channel Realization open source software and extensive channel measurement campaigns were conducted with NIST (National Institute of Standards and Technology) to implement the millimeter wave (mmWave) channel. Our simulation results demonstrate that our proposed scheme outperforms comparison schemes in terms of the accuracy of the signal strength estimation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.5 s.108
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• pp.408-415
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• 2006

This paper suggests an improved system-level model of RF power amplifiers(PAs) including memory effects, and validates the suggested model by analyzing the power spectral density of the output signal with a predistortion linearizer. The original three-box(Wiener-Hammerstein) model uses input and output filters to capture RF frequency response of PAs. The adjacent spectral regrowth that occurs in three-box model can be perfectly removed by Hammerstein structure predistorter. However, the predistorter based on Hammerstein structure achieves limited performance in real PA applications due to other memory effects except RF frequency response. The spectrum of the output signal can be predicted accurately using the suggested model that changes a memoryless block in a three-box model with a memory polynomial. The proposed model accurately predicts the output spectrum density of PA with Hammerstein structure predistorter with less than 2 dB errors over ${\pm}30$ MHz adjacent channel ranges for IEEE 802.11 g WLAN signal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1492-1512
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• 2011

Due to multiple hops, mobility and time-varying channel, supporting delay sensitive real-time traffic in wireless local area network-based (WLAN) mesh networks is a challenging task. In particular for real-time traffic subject to medium access control (MAC) layer control overhead, such as preamble, carrier sense waiting time and the random backoff period, the performance of real-time flows will be degraded greatly. In order to support real-time traffic, an efficient adaptive packet scheduling (APS) scheme is proposed, which aims to improve the system performance by guaranteeing inter-class, intra-class service differentiation and adaptively adjusting the packet length. APS classifies incoming packets by the IEEE 802.11e access class and then queued into a suitable buffer queue. APS employs strict priority service discipline for resource allocation among different service classes to achieve inter-class fairness. By estimating the received signal to interference plus noise ratio (SINR) per bit and current link condition, APS is able to calculate the optimized packet length with bi-dimensional markov MAC model to improve system performance. To achieve the fairness of intra-class, APS also takes maximum tolerable packet delay, transmission requests, and average allocation transmission into consideration to allocate transmission opportunity to the corresponding traffic. Detailed simulation results and comparison with IEEE 802.11e enhanced distributed channel access (EDCA) scheme show that the proposed APS scheme is able to effectively provide inter-class and intra-class differentiate services and improve QoS for real-time traffic in terms of throughput, end-to-end delay, packet loss rate and fairness.

• ETRI Journal
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• v.33 no.2
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• pp.283-286
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• 2011

Path loss plays fundamental roles in system design, spectrum management, and performance evaluation. The traditional path loss model has a slight inconvenience; it depends on the unknown distance. In this letter, we explore the probability distribution function (PDF) of path loss in an indoor office environment by randomizing out the distance variable. It is shown that the resulting PDF is not Gaussian-like but is skewed to the right, and both the PDF and the moments are related to the size of the office instead of the unknown distance. To be specific, we incorporate the IEEE 802.15.4a channel parameters into our model and tabulate the cumulative distribution function with respect to different room sizes. Through a simple example, we show how our model helps a cognitive spectrum user to infer path loss information of primary users without necessarily knowing their transmitter-receiver distance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1337-1358
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• 2015

In this paper, we present an analytical and simulated study on the performance of adaptive vehicular ad hoc networks (VANET) priority based on Transmission Distance Reliability Range (TDRR) and data type. VANET topology changes rapidly due to its inherent nature of high mobility nodes and unpredictable environments. Therefore, nodes in VANET must be able to adapt to the ever changing environment and optimize parameters to enhance performance. However, there is a lack of adaptability in the current VANET scheme. Existing VANET IEEE802.11p's Enhanced Distributed Channel Access; EDCA assigns priority solely based on data type. In this paper, we propose a new priority scheme which utilizes Markov model to perform TDRR prediction and assign priorities based on the proposed Markov TDRR Prediction with Enhanced Priority VANET Scheme (MarPVS). Subsequently, we performed an analytical study on MarPVS performance modeling. In particular, considering five different priority levels defined in MarPVS, we derived the probability of successful transmission, the number of low priority messages in back off process and concurrent low priority transmission. Finally, the results are used to derive the average transmission delay for data types defined in MarPVS. Numerical results are provided along with simulation results which confirm the accuracy of the proposed analysis. Simulation results demonstrate that the proposed MarPVS results in lower transmission latency and higher packet success rate in comparison with the default IEEE802.11p scheme and greedy scheduler scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.378-384
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• 2015

Indoor localization is becoming one of the most important technologies for smart mobile applications with different requirements from conventional outdoor location estimation algorithms. Fingerprinting location estimation techniques based on neural networks have gained increasing attention from academia due to their good generalization properties. In this paper, we propose a novel location estimation algorithm based on an ensemble of multiple neural networks. The neural network ensemble has drawn much attention in various areas where one neural network fails to resolve and classify the given data due to its' inaccuracy, incompleteness, and ambiguity. To the best of our knowledge, this work is the first to enhance the location estimation accuracy in indoor wireless environments based on a neural network ensemble using fingerprinting training data. To evaluate the effectiveness of our proposed location estimation method, we conduct the numerical experiments using the TGn channel model that was developed by the 802.11n task group for evaluating high capacity WLAN technologies in indoor environments with multiple transmit and multiple receive antennas. The numerical results show that the proposed method based on the NNE technique outperforms the conventional methods and achieves very accurate estimation results even in environments with a low number of APs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1498-1509
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• 2004

In this paper, we evaluate the performance of a noncoherent OOK (On-Off Keying) UWB (Ultra Wide Band) system based on power detection with noise power calibration and noise power windowing for ubiquitous sensor network applications in typical indoor wireless channels. Utilizing noise power calibration and noise power windowing, the current noise information can be initially or adaptively provided to determine suitable detection threshold value for signal demodulation. Simulation results show that the noncoherent OOK UWB system using noise power calibration achieves good BER (Bit Error Rate) performance which is favorably comparable to that of the system using the ideal adaptive threshold, while maintaining simple receiver structure. However, despite the serious loss of the data transmission rate, the performance improvement by noise power windowing is not so remarkable. furthermore, these performance results are similarly maintained in BEE 802.15 Task Group 3a UWB indoor channel model, and it is also revealed that the BER performance can be significantly improved by increasing the pulse repetition rate.