Channel Estimation Research Papers - Academia.edu (original) (raw)

This paper investigates the problem of channel quality indicator (CQI) estimation in the context of OFDMA systems in the downlink. The problem of CQI estimation is addressed for SINR-based CQI forms. In this paper, we present a technique for instantaneous SINR estimation which consists in using the channel estimator already present at the receiver to obtain the useful signal levels and signal regeneration (SR) estimator to get the level of interference plus noise. We show that SR estimator has an error floor caused by channel estimation errors, and then we introduce a compensation factor rho in order to remove this error floor. The compensation factor rho is defined as the ratio between the variance of channel estimation errors and the level of interference plus noise at the input of the channel estimator. Thanks to the compensation factor rho we achieve a gain of about 1 dB in term of RMSE for CQI estimation over a wide range of CQI values.

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- Channel Estimation, Link Adaptation

Major river valleys (e.g. Ganga, Brahmaputra, Narmada, Godavari, Kosi etc.) of India have remained as cradles of human livelihood and achievements throughout the course of human history. In the same way, contributing with floods the Damodar valley of eastern India is nurturing its civilization in different phases through almost 3,500 year. Documented history of ruinous extreme floods is more than 347 years old (1665 – 2012) in the Damodar River. It is true that when this river is in the extreme phase, none can withstand against its power. Still we are not now fully capable to manage the adamant nature of river particularly in the monsoon period. Simultaneously the uncertain event, e.g. cloud burst, heavy monsoon rainfall and cyclones etc., and resultant flash floods are not forecast accurately. As the catchment of Damodar has good physiographic and hydro-meteorological potentiality of floods, it is imperative to know the current status of flood probability and risk. So here an attempt is made to investigate the temporal variation (i.e. natural phase – without dams and controlled phase – with dams) of annual peak flows understanding the dam induced flood hydrological changes in the Damodar River. Using the quantitative techniques, viz., Flood Potential Index (FPI), Flash Flood Magnitude Index (FFMI) and Flood Frequency Analysis (FFA), the magnitude of flash floods and channel dimensions are analyzed to derive significant explanation and prediction about the flood risk in the lower segment of Damodar River.

- by Sandipan Ghosh
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- Geography, Environmental Geography, Physical Geography, Hydrology/Hydrography

This paper deals with the robust minimum mean square error
(MMSE) channel estimation for LTE (Long Term Evolution)
downlink OFDM (Orthogonal Frequency Division Multiplexing)
system over time varying mobile environments. Recently robust
estimators are proposed for OFDM systems with block type pilot
structure. These estimators do not require channel correlation
functions for estimation and give robust performance independent
of actual power delay profile (PDP). However, LTE pilot structure
is a combination of both block type and comb type pilot structure.
Hence, there is a need to develop a channel estimator giving robust
performance for LTE system. This allows the system to be
deployed in rural areas having complex mobile environment such
as more mud houses and dense trees. The mean square error
(MSE) performance of the proposed estimator is analyzed with
various power delay profiles applicable to LTE systems. Analytical
expressions are derived for MSE and it is verified that both
analytical and simulation results are exactly matching.

- by Rajeswari Ramanthan
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- Channel Estimation
- by Habib Senol
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- Channel Estimation, Low Complexity
- by IJERA Journal
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- MIMO-OFDM systems, LTE, OFDM, Channel Estimation
- by Mary Ingram
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- Biomedical Engineering, Signal Processing, System Design, Channel Estimation
- by Michele Morelli and +1
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- Multidisciplinary, Channel Estimation, Computer Simulation, Maximum Likelihood
- by IJERA Journal
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- Wireless Communications, Channel Estimation, MIMO-OFDM
- by Steven Blostein
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- Antenna arrays, Channel Estimation, Conference, Bit Error Rate
- by Markku Renfors and +1
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- Engineering, Technology, Computational Complexity, Channel Estimation

In this paper, we analyze the accuracy of indoor localization measurement based on a wireless sensor network. The position estimation procedure is based on the received-signal-strength measurements collected in a real indoor environment. Two different classes of low-computational-effort algorithms based on the centroid concept are considered, i.e., the weighted centroid localization method and the relative-span exponential weighted localization method. In particular, different sources of measurement uncertainty are analyzed by means of theoretical simulations and experimental results.

- by Jeronimo Arenas-Garcia
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- Machine Learning, Signal Processing, Multidisciplinary, Channel Estimation

Millimeter Wave (mmWave) massive Multiple Input Multiple Output (MIMO) systems realizing directive beam-forming require reliable estimation of the wireless propagation channel. However, mmWave channels are characterized by high variability that severely challenges their recovery over short training periods. Current channel estimation techniques exploit either the channel sparsity in the beamspace domain or its low rank property in the antenna domain, nevertheless, they still require large numbers of training symbols for satisfactory performance. In this paper, we present a novel channel estimation algorithm that jointly exploits the latter two properties of mmWave channels to provide more accurate recovery, especially for shorter training intervals. The proposed iterative algorithm is based on the Alternating Direction Method of Multipliers (ADMM) and provides the global optimum solution to the considered convex mmWave channel estimation problem with fast convergence properties.

- by George Alexandropoulos and +2
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- Millimeter Waves, Mobile Radio Channel Estimation, MIMO Systems, Sparse Channel Estimation
- by Mst. Najnin Sultana
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- System Identification, Multidisciplinary, OFDM, Optimization

Channel-dependent scheduling of transmission of data packets in a wireless system is based on measurement and feedback of the channel quality. To alleviate the performance degradation due to simultaneous multiple imperfect channel quality information (CQI), a simple and efficient packet scheduling (PS) algorithm is developed in downlink LTE system for real time traffic. A frequency domain channel predictor based on Kalman filter is first developed to restore the true CQI from erroneous channel quality feedback. Then, a time domain grouping technique employing the joint of Proportional Fair (PF) and Modified Largest Weighted Delay First (M-LWDF) algorithms is used. It was proved this proposal achieves better performance in terms of system throughput and packet loss ratio by simulation results.

- by Leonel Mendes
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- Channel Coding, Antenna arrays, Performance Evaluation, Channel Estimation

This paper investigates the uplink transmission in multi‐cell multi‐user multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The system model considers imperfect channel estimation, pilot contamination (PC), multi‐carrier and multi‐path channels. Analytical expressions are first presented on the mean square error (MSE) of two classical channel estimation algorithms (i.e., least square (LS) and minimum mean square error (MMSE)) in the presence of PC. Then, a simple H‐inf channel estimation approach is proposed in order to have good suppression to PC.
" Its a analysis and implementation of paper written by Peng Xu, Jiangzhou Wang, Senior Member, IEEE, Jinkuan Wang, Member, IEEE, Feng Qi "

- by Sivadeep Reddy
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- MIMO-OFDM systems, MIMO Systems, Channel Estimation, Multi-User MIMO Communication

In this paper, ultra-wideband (UWB) channel estimation based on the theory of compressive sensing (CS) is developed. The proposed approach relies on the fact that transmitting an ultra-short pulse through a multipath UWB channel leads to a received UWB signal that can be approximated by a linear combination of a few atoms from a pre-defined dictionary, yielding thus a sparse representation of the received UWB signal. The key in the proposed approach is in the design of a dictionary of parameterized waveforms (atoms) that closely matches the information-carrying pulseshape leading thus to higher energy compaction and sparse representation, and, therefore higher probability for CS reconstruction. Two approaches for UWB channel estimation are developed under a data-aided framework. In the first approach, the CS reconstruction capabilities are exploited to recover the composite pulse-multipath channel from a reduced set of random projections. This reconstructed signal is subsequently used as a referent template in a correlator-based detector. In the second approach, from a set of random projections of the received pilot signal, the Matching Pursuit algorithm is used to identify the strongest atoms in the projected signal that, in turn, are related to the strongest propagation paths that composite the multipath UWB channel. A Rake like receiver uses those atoms as templates for the bank of correlators in the detection stage. The bit error rate performances of the proposed approaches are analyzed and compared to that of traditional correlator-based detector. Extensive simulations show that for different propagation scenarios and UWB communication channels, detectors based on CS channel estimation outperform traditional correlator using just 1/3 of the sampling rate leading thus to a reduced use of analog-to-digital resources in the channel estimation stage.

- by José Paredes
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- Compressed Sensing, Channel Estimation, Bit Error Rate, Communication Channels
- by Minhua Ding and +1
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- Multidisciplinary, Optimization Problem, Channel Estimation, Mean square error
- by Uyanga Perenlei
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- Channel Coding, Modulation, Digital Radio Mondiale, Channel Estimation
- by Vaibhav Mishra
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- Engineering, Statistics, Technology, System Identification

In OFDM (Orthogonal frequency division multiplexing) systems, channel estimation and channel
equalization play a key role in overcoming distortions caused by phenomena like fading, delay spread and
multipath effect. In this paper, channel estimation and equalization techniques are analyzed to improve the
performance of OFDM system. The channel estimation techniques considered here are estimation using
wiener filter and frequency domain approach. Prior Channel estimation leads to simple equalization. The
channel equalization techniques employed here are based on LMS algorithm and one tap frequency domain
equalization, under different channels; AWGN, Rayleigh and Rician channels. Eye patterns for different
channels are compared in simulation. It is observed from simulation that wiener filter provides better
estimation and OFDM performance is better under AWGN channel than fading channels. SER curves
shows 6dB improvement in AWGN performance than fading channels to achieve 0.1 SER. In addition, MSE
performance shows fast convergence for AWGN channel.

- by Dirk Slock
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- Channel Estimation, Software Requirement Specification
- by Joseph R Cavallaro
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- Algorithms, Computational Complexity, Computer Hardware, Channel Estimation

Underwater communication is one of the challenging fields in communication engineering with wired and wireless communication. In underwater communication there are several possibilities for mitigating terrestrial communication limitations. Familiar methods for underwater communication are using radio waves, optical fibers and acoustic waves. Limitation of short distance range of communication with RF and fiber, low frequency sound waves are used here as the medium and also acoustic waves are capable of withstanding ambient noises and vibrations in water.
This project intend to the design of an underwater acoustic communication system. For an underwater communication cost is not a factor for initial deployment of the system as the frequent maintenance is not practically possible. To design a reliable communication system the main aims are long distance, secure and accurate. Here such a system is selected as existing system and it is analyzed. An amplifier and forward relay assisted system is considered as the existing system to study about underwater acoustic communication system in detail for designing a reliable system. One of the specialty of this paper is it covers almost all fields in communication engineering, especially signal processing, wireless communication, estimation and detection, etc.
The main focus of this paper is sparse channel estimation and equalization with AF relaying for underwater cooperative systems based on OFDM. For the channel estimation Matching Pursuit (MP) algorithm is used in combination with maximum a posteriori probability (MAP) based SAGE technique. This algorithm is low complex for good performance channel estimation and it will provide a better symbol error rate and can overcome the mismatching effects of Doppler shift. In simulation results for CGM-MP-SAGE algorithm, Doppler effects and multipath system for BPSK modulation are analyzed in terms of SER performance and average MSE based on SNR values. This system has a poor reliability in terms of practical implementation. Thus a new system is proposed to compensate the drawbacks and for practical implementation. Some reliable approaches can be used by including different ideas such as compress and forward relay can be used to increase the data rate and avoiding error, instead of AF relaying. For frequency and time analyzing pilot based estimation with PN sequence can be used.
In addition to this for providing high diversity MIMO system can be integrated. Zero force equalizer can be provided and adaptive filter is used for equalization, here RLS filter is used to avoid interferences. For the removal of channel error and burst error, a channel encoder and interleaver is used respectively. More important a fast converging estimation technique is used instead of MAP is MMSE. Minimum mean square error estimation is used, as it is suitable for practical deployment in underwater with excellent SNR performance results than MP-SAGE algorithm.
As UWAC system has to suffer from fading, interferences and noises, the system should design in such a way that to compensate these problems. So interference alignment is included to improve capacity, power allocation is provided with SVD and DPC algorithms for separate SNR regions. When the energy efficiency is maximized, the capacity of the system increases. For high SNR singular value decomposition is used with water filling power adaptation algorithm and EE is optimized. The optimization of EE and power allocation is easy to implement as noise and interference is less.
For moderate SNR regions, the power is less so by using DPC algorithm the distorted or low power signal at receiver can be boosted so power can increased and thereby energy efficiency get maximized. This work introduces a design for reliable underwater communication system using acoustic waves is implementing with CGM-MP-MMSE estimation and the capacity of the system is improving for variable SNR regions with SVD and DPC algorithms.

- by harish reddy
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- Channel Estimation, Cost effectiveness, Access Point, Indoor Environment
- by Carlos Pirmez
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- Geology, Geophysics, Migration, Channel Estimation

Severe tropical weather dynamics impairments on the earth-sky signal quality at the Ku-band relative to temperate weather increase the demand for land mobile satellite (LMS) channel characterization and modeling specific to tropical regions. Variation in weather dynamics decreases the accuracy of the existing LMS channel models if applied to the tropics. This paper presents a tropical weather-aware LMS channel model that can be applied at areas with diverse atmospheric (rain, clouds, and tropospheric scintillation) and mobility impairments. The proposed tropical-LMS channel (TRO-LMSC) model is designed based on actual experimental measurements conducted in a tropical area. The TRO-LMSC model involves multipath design, mobility model, rain impairment model, cloud impairment model, tropospheric scintillation model, and link budget module (LBM). The proposed model shows improved channel modeling accuracy and comprehensiveness with relatively less root mean square error (rmse), compared with existing models. Consequently, this improvement enhances the identification of the type and performance of the fade mitigation technique, the management of available communication resources, and the reliability and efficiency of the communication services.

- by Rajeswari Ramanthan
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- Wireless Communications, ML, Channel Estimation, MMSE
- by Bilal Khan
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- Computer Science, Distributed Computing, Fuzzy Logic, Cognitive radio

In this paper we investigate the bit error rate (BER) performance of orthogonal frequency division
multiplexing (OFDM) wireless communication system with the implementation of LS-Interpolation-based
comb-type pilot symbol-assisted channel estimation algorithm over frequency selective multi-path Rayleigh
fading channel. The Least square (LS) method is used for the estimation of channel at pilot frequencies
while different interpolation techniques such as low-pass interpolation, cubic interpolation, spline cubic
interpolation, linear interpolation and FFT interpolation are employed to interpolate the channel at data
frequencies. In signal mapping, the OFDM system incorporates M-ary phase-shift keying (M-PSK) and Mary
quadrature amplitude modulation (M-QAM) digital modulation schemes. Matlab simulations are
carried out to analyze the performance of the developed OFDM system with the employment of comb-pilot
based channel estimation algorithms for various digital modulations in Rayleigh fading environment. The
impact of Doppler frequency and number of channel taps on the BER performance is also investigated.

In this paper, we have evaluated various methods of time-frequency-selective fading channels estimation in OFDM system and some of them improved under time varying conditions. So, these different techniques will be studied through different algorithms and for different schemes of modulations (16 QAM, BPSK,QPSK,…). Channel estimation gathers different schemes and algorithms, some of them are dedicated for slowly time varying (such as block type arrangement insertion, Bayesian Cramer-Rao Bound, Kalman estimator,Subspace estimator,…) whereas the others concern highly time varying channels (comb type insertion,…) . There are others methods that are just suitable for stationary channels like blind or semi blind estimators.For this aim, diverse algorithms were used for these schemes such as Least Squares estimator LS, Least Minimum Squares LMS, Minimum Mean-Square-ErrorMMSE, Linear Minimum Mean-Square-Error LMMSE, Maximum Likelihood ML,…to refine estimators shown previously.

- by Maha George
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- Adaptive Filtering, Channel Estimation, Ofdm Systems
- by Colin Reinhardt and +1
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- Digital Holography, LiDAR, Modeling and Simulation, Signal Detection Theory
- by André L. F. de Almeida
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- Engineering, Technology, Signal Processing, Performance Analysis
- by Ali M . Al-Saegh and +2
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- Satellite Communications, Atmospheric Water Vapor, Channel Estimation, Rain Attenuation

In the last few years Compressed Sampling (CS) has been well used in the area of signal processing and image compression. Recently, CS has been earning a great interest in the area of wireless communication networks. CS exploits the sparsity of the signal processed for digital acquisition to reduce the number of measurement, which leads to reductions in the size, power consumption, processing time and processing cost. This article presents application of CS for the spectrum sensing and channel estimation in Cognitive Radio (CR) networks. Basic approach of CS is introduced first, and then scheme for spectrum sensing and channel estimation for CR is discussed. First, fast and efficient compressed spectrum sensing (CSS) scheme is proposed to detect wideband spectrum, where samples are taken at sub-Nyquist rate and signal acquisition is terminated automatically once the samples are sufficient for the best spectral recovery and then, after the spectrum sensing, in the second phase notion of multipath sparsity is formalized and a novel approach based on Orthogonal Matching Pursuit (OMP) is discussed to estimate sparse multipath channels for CR networks. The effectiveness of the proposed scheme is demonstrated through comparisons with the existing conventional spectrum sensing and channel estimation methods.

- by zhuo chen
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- Engineering, Technology, Channel Coding, Fading Channel

Channel routing is a key problem in VLSI physical design. The main goal of the channel routing problem is to reduce the area of an IC chip. If we concentrate on reducing track number in channel routing problem then automatically the area of an IC chip will be reduced. Here, we propose a new algorithm to reduce the number of tracks using four layers (two horizontal layers and two vertical layers). To be more specific, through this algorithm we convert a two-layer channel routing problem into a four-layer channel routing problem using VCG of the channel. Next, we show the experimental results and graphical structure of that solution.

- by Michele Morelli and +1
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- Distributed Computing, Channel Estimation, Power System State Estimation, Bit Error Rate

A 20 GHz channel emulator for broadband
differential data links has been developed using a trace overlaid
with lossy materials and a two stage programmable Finite
Impulse Response (FIR) filter. It allows to emulate the main
channel and the cross-talk in the data links. The hardware design and emulation procedure are described. The emulated channel matches the target channel, validating the design methodology.

- by Atieh Talebzadeh and +1
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- Genetic Algorithms, Optimization techniques, Ultra Wideband System Design, RF and Microwave Systems
- by min ha
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- Computational Complexity, Mobile Communication, Algorithm, Parameter estimation