• Title/Summary/Keyword: Signal Optimization

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Group Power Constraint Based Wi-Fi Access Point Optimization for Indoor Positioning

  • Pu, Qiaolin;Zhou, Mu;Zhang, Fawen;Tian, Zengshan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.5
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    • pp.1951-1972
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    • 2018
  • Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

Optimization Method of Kalman Filter Parameters Based on Genetic Algorithm for Improvement of Indoor Positioning Accuracy of BLE Beacon (BLE Beacon의 실내 측위 정확도 향상을 위한 Genetic Algorithm 기반 Kalman Filter Parameters 최적화 방법)

  • Kim, Seong-Chang;Kim, Jin-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.11
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    • pp.1551-1558
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    • 2021
  • Beacon signals used in indoor positioning system are reflected and distorted, resulting in noise signals. KF(Kalman Filter) has been widely used to remove this noise. In order to apply the KF, optimization process considering the signal type, signal strength, and environmental elements of each product is required. In this paper, we propose a solution to the optimization problem of KF Parameters using GA(Genetic Algorithm) in BLE(Bluetooth Low Energy) Beacon-based indoor positioning system. After optimizing KF Parameters by applying the proposed technique with a certain distance between Beacon and receiver, we compared the estimated distance passed through KF with the unfiltered distance. The proposed technique is expected to reduce the time required and improve accuracy of KF Parameters optimization in an indoor positioning system based on RSSI (Received Signal Strength Indication).

Development of A System Optimum Traffic Control Strategy with Cell Transmission Model (Cell Transmission 이론에 근거한 시스템최적 신호시간산정)

  • 이광훈;신성일
    • Journal of Korean Society of Transportation
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    • v.20 no.5
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    • pp.193-206
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    • 2002
  • A signal optimization model is proposed by applying the Cell-Transmission Model(CTM) as an embedded traffic flow model to estimate a system-optimal signal timing plan in a transportation network composed of signalized intersections. Beyond the existing signal-optimization models, the CTM provides appropriate theoretical and practical backgrounds to simulate oversaturation phenomena such as shockwave, queue length, and spillback. The model is formulated on the Mixed-Integer Programming(MIP) theory. The proposed model implies a system-optimal in a sense that traffic demand and signal system cooperate to minimize the traffic network cost: the demand departing from origins through route choice behavior until arriving at destinations and the signal system by calculating optimal signal timings considering the movement of these demand. The potential of model's practical application is demonstrated through a comparison study of two signal control strategies: optimal and fixed signal controls.

A Study of Traffic Signal Timing Optimization Based on PSO-BFO Algorithm (PSO-BFO 알고리즘을 통한 교통 신호 최적화 연구)

  • Hong Ki An;Gimok Bae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.6
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    • pp.182-195
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    • 2023
  • Recently, research on traffic signal control using artificial intelligence algorithms has been receiving attention, and many traffic signal control models are being studied. However, most studies either focused on independent intersections or are theoretical studies that calculate signal cycle length according to changes in traffic volume. Therefore, this study was conducted on a signalized intersection - roundabout in Gajwa-ro. The Particle Swarm Optimization - Bacterial Foraging Optimization (PSO-BFO) algorithm was proposed, which is developed from the GA and PSO algorithms for minimizing congestion at two intersections. As a result, optimum cycle length was determined to be 158 seconds. The Verkehr In Stadten - SIMulationsmodell (VISSIM) results showed that there was 3.4% increased capacity, 8.2% reduced delay and 8.3% reduced number of stops at the Gajwa-ro signalized intersection. Additionally, at the roundabout, a 9.2% increase in capacity, a 7.1% reduction in delay, and a 27.2% decrease in the number of stops was observed.

Analysis of Joint Multiband Sensing-Time M-QAM Signal Detection in Cognitive Radios

  • Tariq, Sana;Ghafoor, Abdul;Farooq, Salma Zainab
    • ETRI Journal
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    • v.34 no.6
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    • pp.892-899
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    • 2012
  • We analyze a wideband spectrum in a cognitive radio (CR) network by employing the optimal adaptive multiband sensing-time joint detection framework. This framework detects a wideband M-ary quadrature amplitude modulation (M-QAM) primary signal over multiple nonoverlapping narrowband Gaussian channels, using the energy detection technique so as to maximize the throughput in CR networks while limiting interference with the primary network. The signal detection problem is formulated as an optimization problem to maximize the aggregate achievable secondary throughput capacity by jointly optimizing the sensing duration and individual detection thresholds under the overall interference imposed on the primary network. It is shown that the detection problems can be solved as convex optimization problems if certain practical constraints are applied. Simulation results show that the framework under consideration achieves much better performance for M-QAM than for binary phase-shift keying or any real modulation scheme.

Time- and Frequency-Domain Optimization of Sparse Multisine Coefficients for Nonlinear Amplifier Characterization

  • Park, Youngcheol;Yoon, Hoijin
    • Journal of electromagnetic engineering and science
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    • v.15 no.1
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    • pp.53-58
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    • 2015
  • For the testing of nonlinear power amplifiers, this paper suggests an approach to design optimized multisine signals that could be substituted for the original modulated signal. In the design of multisines, complex coefficients should be determined to mimic the target signal as much as possible, but very few methods have been adopted as general solutions to the coefficients. Furthermore, no solid method for the phase of coefficients has been proven to show the best resemblance to the original. Therefore, in order to determine the phase of multisine coefficients, a time-domain nonlinear optimization method is suggested. A frequency-domain-method based on the spectral response of the target signal is also suggested for the magnitude of the coefficients. For the verification, multisine signals are designed to emulate the LTE downlink signal of 10 MHz bandwidth and are used to test a nonlinear amplifier at 1.9 GHz. The suggested phase-optimized multisine had a lower normalized error by 0.163 dB when N = 100, and the measurement results showed that the suggested multisine achieved more accurate adjacent-channel leakage ratio (ACLR) estimation by as much as 12 dB compared to that of the conventional iterative method.

A Study on Operation Methodology of A Signalized Intersection Based on Optimization of Lane-Uses (차로배정 최적화를 고려한 신호교차로 운영방안에 관한 연구)

  • Kim, Ju Hyun;Shin, Eon Kyo
    • International Journal of Highway Engineering
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    • v.15 no.6
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    • pp.125-133
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    • 2013
  • PURPOSES : The purpose of this study is to propose delay-minimizing operation methodology of a signalized intersection based upon optimization of lane-uses on approaching lanes for an intersection. METHODS : For the optimization model of lane-uses, a set of constraints are set up to ensure feasibility and safety of the lane-uses, traffic flow, and signal settings. Minimization of demand to saturation flow ratio of a dual-ring signal control system is introduced to the objective function for delay minimization and effective signal operation. Using the optimized lane-uses, signal timings are optimized by delay-based model of TRANSYT-7F. RESULTS : It was found that the proposed objective function is great relation with delay time for an intersection. From the experimental results, the method was approved to be effective in reducing delay time. Especially, cases for two left-turn lanes reduced greater delays than those for a left turn lane. It is noticed that the cases for different traffic volume by approach reduced greater delays than those for the same traffic volume by approach. CONCLUSIONS : It was concluded that the objective function is proper for lane-uses optimizing model and the operation method is effective in reducing delay time for signalized intersections.

A Study on Improvement of Run-Time in KS-SIGNAL, Traffic Signal Optimization Model for Coordinated Arterials (간선도로 연동화 신호최적화 모형 KS-SIGNAL의 수행속도 향상을 위한 연구)

  • 박찬호;김영찬
    • Journal of Korean Society of Transportation
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    • v.18 no.4
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    • pp.7-18
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    • 2000
  • KS-SIGNAL, a traffic signal optimization model for coordinated arterials, is an optimization model using the mixed integer linear Programming that minimizes total delay on arterials by optimizing left-turn Phase sequences. However, the Previous version of KS-SIGNAL had a difficulty in reducing computation speed because the related variables and constraints multiply rapidly in accordance with the increase of intersections. This study is designed to propose a new model, improving optimizing computation speed in KS-SIGMAl, and evaluate it. This Paper Puts forth three kinds of methodological approaches as to achieve the above goals. At the first step to reduce run-time in the proposed model objective function and a few constraints are Partially modified, which replaces variable in related to queue clearance time with constant, by using thru-movements at upstream intersection and the length of red time at downstream intersection. The result shows that the run-time can be reduced up to 70% at this step. The second step to load the library in LINDO for Windows, in order to solve mixed integer linear programming. The result suggests that run-time can be reduced obviously up to 99% of the first step result. The third step is to add constraints in related to left-turn Phase sequences. The proposed methodological approach, not optimizing all kinds of left-turn sequences, is more reasonable than that of previous model , only in the view of reducing run-tim. In conclusion, run-time could be reduced up to 30% compared with the second results. This Proposed model was tested by several optimization scenarios. The results in this study reveals that signal timing plan in KS-SIGNAL is closer to PASSER-II (bandwidth maximizing model) rather than to TRANSYT-7F(delay minimizing model).

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Adaptive Nulling Algorithm to Reduce the Main-Beam Distortion in Single-Port Phased Array Antenna (단일포트 위상배열안테나에서 주빔 왜곡 현상을 줄이기 위한 적응형 널링 알고리즘)

  • Seo, Jongwoo;Park, Dongchul
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.9
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    • pp.808-816
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    • 2016
  • In this paper, a new technique and cost function which can be to classify jamming signal and target signal from the spectral distribution of received signal in order to minimize the main beam distortion of target signal and to form nulls in the direction of jamming signal in array antennas of single port system is proposed. The proposed cost function is applied to the adaptive algorithm which has the fast convergence and stable nulling performance through the combination of the PSO(Particle Swam Optimization) algorithm and the gradient-based perturbation algorithm, which shows stable nulling performance adaptively even under the moving jamming signal where the incident direction of the jamming signal is changing with time.

Fixed-point optimization utility for digital signal processing programs (디지탈 신호처리용 고정 소수점 최적화 유틸리티)

  • 김시현;성원용
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.9
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    • pp.33-42
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    • 1997
  • Fixed-point optimization utility software that can aid scaling and wordlength determination of digital signal processign algorithms written in C or C$\^$++/ language is developed. This utility consists of two programs: the range estimator and the fixed-point simulator. The former estimates the ranges of floating-point variables for automatic scaling purpose, and the latter translates floating-point programs into fixed-point equivalents for evaluating te fixed-point performance by simulation. By exploiting the operator overloading characteristics of C$\^$++/ language, the range estimation and the fixed-point simulation can be conducted just by modifying the variable declaration of the original program. This utility is easily applicable to nearly all types of digital signal processing programs including non-linear, time-varying, multi-rate, and multi-dimensional signal processing algorithms. In addition, this software can be used for comparing the fixed-point characteristics of different implementation architectures.

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