Channel estimation based on adaptive neuro-fuzzy inference system in OFDM

被引：0
|
作者：
Seyman, M. Nuri [1 ]
Taspinar, Necmi [2 ]
机构：
[1] Kirikkale Univ, Kirikkale Vocat Tech Sch, Kirikkale, Turkey
[2] Erciyes Univ, Dept Elect & Elect Engn, TR-38039 Kayseri, Turkey
来源：
IEICE TRANSACTIONS ON COMMUNICATIONS | 2008年 / E91B卷 / 07期
关键词：
OFDM; channel estimation; ANFIS; channel impulse response (CIR);
D O I：
10.1093/ietcom/e9l-b.7.2426
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this letter we purpose adaptive neuro-fuzzy inference system (ANFIS) for channel estimation in orthogonal frequency division multiplexing (OFDM) systems. To evaluate the performance of this estimator, we compare the ANFIS with least square (LS) algorithm, minimum mean square error (MMSE) algorithm by using bit error rate (BER) and mean square error (MSE) criterias. According to computer simulations the performance of ANFIS has better performance than LS algorithm and close to MMSE algorithm. Besides there is unnecessity to send pilot when used the ANFIS.
引用
收藏
页码：2426 / 2430
页数：5
相关论文
共 50 条
  • [41] ESTIMATION OF SUBSURFACE STRATA OF EARTH USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)
    Srinivas, Y.
    Raj, A. Stanley
    Oliver, D. Hudson
    Muthuraj, D.
    Chandrasekar, N.
    [J]. ACTA GEODAETICA ET GEOPHYSICA HUNGARICA, 2012, 47 (01): : 78 - 89
  • [42] Estimation of natural gases water content using adaptive neuro-fuzzy inference system
    Baghban, Alireza
    Kashiwao, Tomoaki
    Bahadori, Meysam
    Ahmad, Zainal
    Bahadori, Alireza
    [J]. PETROLEUM SCIENCE AND TECHNOLOGY, 2016, 34 (10) : 891 - 897
  • [43] Composition Estimation of Reactive Batch Distillation by Using Adaptive Neuro-Fuzzy Inference System
    Khazraee, S. M.
    Jahanmiri, A. H.
    [J]. CHINESE JOURNAL OF CHEMICAL ENGINEERING, 2010, 18 (04) : 703 - 710
  • [44] Neuro-Fuzzy Evaluation of the Software Reliability Models by Adaptive Neuro Fuzzy Inference System
    Milos Milovancevic
    Aleksandar Dimov
    Kamen Boyanov Spasov
    Ljubomir Vračar
    Miroslav Planić
    [J]. Journal of Electronic Testing, 2021, 37 : 439 - 452
  • [45] Estimation of subsurface strata of earth using Adaptive Neuro-Fuzzy Inference System (ANFIS)
    Y. Srinivas
    A. Stanley Raj
    D. Hudson Oliver
    D. Muthuraj
    N. Chandrasekar
    [J]. Acta Geodaetica et Geophysica Hungarica, 2012, 47 : 78 - 89
  • [46] Contact positions estimation of sensing structure using adaptive neuro-fuzzy inference system
    Petkovic, Dalibor
    Issa, Mirna
    Pavlovic, Nenad D.
    Zentner, Lena
    Daud, Md Nor Ridzuan
    Shamshirband, Shahaboddin
    [J]. KYBERNETES, 2014, 43 (05) : 783 - 796
  • [47] Estimation of the Elemental Composition of Biomass Using Hybrid Adaptive Neuro-Fuzzy Inference System
    Olatunji, Obafemi O.
    Akinlabi, Stephen
    Madushele, Nkosinathi
    Adedeji, Paul A.
    [J]. BIOENERGY RESEARCH, 2019, 12 (03) : 642 - 652
  • [48] Adaptive Neuro-Fuzzy Inference System in Fuzzy Measurement to Track Association
    Tafti, Abdolreza Dehghani
    Sadati, Nasser
    [J]. JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 2010, 132 (02): : 1 - 8
  • [49] Neuro-Fuzzy Evaluation of the Software Reliability Models by Adaptive Neuro Fuzzy Inference System
    Milovancevic, Milos
    Dimov, Aleksandar
    Spasov, Kamen Boyanov
    Vracar, Ljubomir
    Planic, Miroslav
    [J]. JOURNAL OF ELECTRONIC TESTING-THEORY AND APPLICATIONS, 2021, 37 (04): : 439 - 452
  • [50] Grid Company Risk Management System Based on Adaptive Neuro-Fuzzy Inference
    Khalyasmaa, A. I.
    Dmitriev, S. A.
    Valiev, R. T.
    [J]. PROCEEDINGS OF 2017 XX IEEE INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND MEASUREMENTS (SCM), 2017, : 892 - 895
12345