Enhanced Channel Estimation Research Articles

Zero Padding or Cyclic Prefix: Evaluation for Non-Orthogonal Signals

The debate of using zero padding (ZP) instead of a cyclic prefix (CP) for enhancing channel estimation and equalization performance is a recurring topic. This is particularly true for orthogonal signals, such as orthogonal frequency division multiplexing (OFDM). Yet, there are far fewer studies evaluating the impact of ZP and CP in non-orthogonal systems. Such systems have the added complexity of self-induced interference rendering channel estimation and equalization more challenging. For this reason, this work proposes a new channel estimation and equalization technique for non-orthogonal systems, which combines ZP with an orthogonal demodulator. Results show that the multipath components that appear in the ZP part can be used to enhance performance when compared to the CP approach.

Pilot Design for BEM-Based Channel Estimation in Doubly Selective Channel

This paper investigates pilot design for enhanced channel estimation in single carrier communication systems over doubly-selective channels (DSC). Our contribution is twofold: first, we propose to use Huffman sequences as pilot clusters with low peak-to-average power ratio (PAPR), yet with good channel estimation performance when periodic pilot placement is adopted; second, we propose a low-complexity pilot placement strategy based on the analysis of the complex-exponential basis expansion model (CE-BEM) of the DSC. The latter leads to improved channel estimation performance with useful insights for pilot placement.

Demonstration of a 2.34 Gbit/s Real-Time Single Silicon-Substrate Blue LED-Based Underwater VLC System

We develop a real-time discrete multi-tone (DMT) transceiver based on field programmable gate array (FPGA) chips for a single chip silicon-substrate light-emitting diode (LED) based underwater visible light communication (UVLC). On-chip resource usages are analyzed and discussed. To improve bit error rate (BER) performance, a novel channel estimation technique utilizing hybrid inter-symbol frequency-averaging (Inter-SFA) and intra-symbol frequency-averaging (Intra-SFA) is proposed and investigated. The real-time DMT transceiver is experimentally verified in a silicon substrate blue LED-based UVLC system with a 1.2 m underwater link. By using the enhanced channel estimation, a gross bit rate of 2.34 Gbit/s real-time DMT signal over 1.2 m underwater transmission can be achieved with the BER of 3.5 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> . What's more, multiple-symbol interleaved Reed-Solomon (RS) codes are employed to further improve BER performance. The real-time measured post-FEC BER of the DMT-UVLC with multiple-symbol interleaved RS (255, 191) codes can be improved by more than six orders of magnitude. As a result, error-free (less than 1 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−9</sup> ) transmission is observed in our real-time experiment. Furthermore, 1.485 Gbit/s 720p high-definition video underwater transmission is successfully demonstrated. To the best of our knowledge, it is the first time to demonstrate a real-time LED-based UVLC system with DMT modulation beyond Gbit/s.

Enhanced channel estimation in OFDM systems with neural network technologies

Orthogonal frequency division multiplexing (OFDM) provides an effective and low complexity means of eliminating inter-symbol interference for transmission over frequency selective fading channels. In OFDM systems, channel state information (CSI) is required for the OFDM receiver to perform coherent detection or diversity combining, if multiple transmit and receive antennas are deployed. In practice, CSI can be reliably estimated at the receiver by transmitting pilots along with data symbols. In this paper, we investigate and compare various efficient pilot-based channel estimation schemes by neural network technologies for OFDM systems. We present further the application of functional link neural fuzzy network (FLNFN) for channel estimation in the investigated OFDM systems. We compared bit error rates of the proposed neural network with that of the other neural network technologies, the least square (LS) algorithm, and the minimum mean square error (MMSE) algorithm. Our results demonstrate that the proposed FLNFN algorithm can enhance the performance of channel estimation in existing OFDM channel environments.

An enhanced channel estimation technique for CDD OFDM system over time varying channels

Cyclic delay diversity (CDD), employing multiple antennas provides increased frequency-selectivity and thereby achieves frequency diversity using forward error correction in orthogonal frequency division multiplexing (OFDM). However, channel estimation of CDD OFDM becomes crucial over frequency-selective fading channels. In this paper, we propose a low-complexity channel estimation technique for CDD OFDM systems over time-varying channels using basis expansion model. We first analyze the frequency correlation of CDD OFDM channels and then design scattered pilot structure for estimating the channel coefficients. In the proposed channel estimator, Slepian sequences are employed estimate the channel impulse response by exploiting the frequency correlation of CDD OFDM over time-varying channel. Simulation results demonstrated that the proposed channel estimator achieves better mean square error and bit-error-rate performance compared with that of existing methods over time-varying channels.

LTE 기반 V2V 통신에서 향상된 채널 추정 기법에 대한 연구

LTE 기반 V2V 통신에서 향상된 채널 추정 기법에 대한 연구

Enhanced Channel Estimation Algorithm for Dedicated Short-Range Communication Systems

The Dedicated Short-Range Communication (DSRC) has been widely accepted as a promising wireless technology for enhancing traffic safety. In such DSRC-based vehicle-to-vehicle (V2V) communication systems, because of the extremely time-varying characteristic of wireless propagation channels, accurate channel estimation is essential for reliable information exchange between vehicles. In this paper, the characteristics of the propagation channel and several traditional channel estimation schemes for V2V communications are reviewed. Then, a delay-based channel-frequency-response decomposition scheme is proposed to estimate and predict the double-selective V2V channel while adhering to the IEEE 802.11p standard. The proposed method achieves a more favorable performance than the traditional methods in V2V scenarios by combining the least square estimation in the frequency domain with the linear prediction in time domain. The performance advantages of the proposed scheme are verified by the simulation results from three typical scenarios. Furthermore, a reference design on a field-programmable gate array for the proposed channel estimation scheme is presented for the purpose of demonstrating its implementation feasibility and complexity.

Spatial DCT-Based Channel Estimation in Multi-Antenna Multi-Cell Interference Channels

This work addresses channel estimation in multiple antenna multicell interference-limited networks. Channel state information (CSI) acquisition is vital for interference mitigation. Wireless networks often suffer from multicell interference, which can be mitigated by deploying beamforming to spatially direct the transmissions. The accuracy of the estimated CSI plays an important role in designing accurate beamformers that can control the amount of interference created from simultaneous spatial transmissions to mobile users. Therefore, a new technique based on the structure of the spatial covariance matrix and the discrete cosine transform (DCT) is proposed to enhance channel estimation in the presence of interference. Bayesian estimation and least squares estimation frameworks are introduced by utilizing the DCT to separate the overlapping spatial paths that create the interference. The spatial domain is thus exploited to mitigate the contamination which is able to discriminate across interfering users. Gains over conventional channel estimation techniques are presented in our simulations which are also valid for a small number of antennas.

MIMO-OFDM with Enhanced Channel Estimation based on DFT Interpolation

In practical wireless communication systems, the transmitter send the information out through a multipath fading channel. At the receiver side, the received information distorted by the channel characteristic (due to multipath fading). So, in order to recover the transmitted information accurately, the channel effect must be known at the receiver. In this paper channel estimation for STBC-MIMO-OFDM system has been investigated by implementing the most popular channel estimators least Square (LS) and Minimum Mean Error Square (MMSE) both based on comb type pilot arrangement to estimate the channel effect at pilot locations, and channel interpolation between pilot locations was done using linear interpolation. The performance of LS and MMSE estimators can be improved by using DFT-based estimation technique. LS and MMSE estimator have been implemented with and without DFT-based estimation technique to estimate the channel effect for STBC-MIMO-OFDM system and compare their performance by measuring the bit error rate BER with QAM as modulation scheme and for different MIMO antenna configurations, also the channel between each antenna pair is assumed to be multipath Rayleigh Slow fading channel based on Clark's model. General Terms Channel estimation, communication, DFT algorithms.

Iterative receiver with soft‐input‐based‐channel estimation for orthogonal frequency division multiplexing‐interleave division multiple access systems

This article presents two sets of channel estimation methods that employ soft input from the decoder to enhance channel estimation process for orthogonal frequency division multiplexing -interleave division multiple access (OFDM-IDMA) system. The first channel estimation scheme exploits both time and frequency domains for channel estimation and prediction. The estimator exploits turbo principle while using iterative based sequential linear minimum mean square error (ISLMMSE) for channel transfer function (CTF) estimation, and regularised variable step size normalised least mean square (l1-VSSNLMS) algorithm for channel impulse response (CIR) prediction. The channel estimation scheme exchanges information with the Multi-User Detector (MUD), and also employs soft information feedback from the decoder for the enhancement of channel estimation. The second iterative channel estimation scheme, in time domain, is based on regularised noise power estimate-based variable forgetting factor recursive least square (l1-NPEVFF-RLS)-based CIR estimator. The performances of the proposed estimators are documented through computer simulation. Their comparative performances with other schemes in the literature are presented in this article. From the simulation results, the two proposed channel estimators exhibit better performance in comparison with other schemes in the literature, but with higher computational complexities. However, of the two proposed methods, the l1-NPEVFF-RLS-based CIR estimator that exhibits almost the same performance as the combined ISLMMSE-based CTF estimator and l1-VSSNLMS-based predictor exhibits lower computational complexity.

A Sparsity Enhanced Channel Estimation Algorithm Based on Compressed Sensing in MIMO-OFDM Systems

基于压缩感知(Compressed Sensing, CS)的信道估计可以达到减少导频的目的，但在频-时域信道矩阵到时延-多普勒域的稀疏变换中存在谱泄漏现象，影响了信道矩阵的稀疏性和估计的均方误差(MSE)性能。为此该文对信道的稀疏性进行研究，提出一种时域加窗的稀疏优化CS信道估计算法。通过对时域加窗，所提算法抑制了由离散截断导致的多普勒域泄漏，再据此设计出观测矩阵，以此方式增强信道在时延-多普勒域的稀疏性，并实现对稀疏的信道矩阵更为准确的重构，达到改善信道估计MSE性能的目的。仿真结果表明随信噪比的增大，加窗CS算法相比无窗CS算法有效改善了信道估计的性能。

An Enhanced Channel Estimation with Partial Interference Cancelation for MU-MIMO System

In this letter, we propose an enhanced channel estimation method for multi-user multiple-input multiple output (MU-MIMO) transmission in long term evolution (LTE)-Advanced system. The proposed method partially estimates and eliminates the interference using simple matrix operations. After that, we apply an iterative channel estimation scheme. Due to the improvement of initial channel estimation performance, the proposed channel estimation method has significantly large performance gain compared to conventional method.

On the Gain of Joint Processing of Pilot and Data Symbols in Stationary Rayleigh Fading Channels

In many typical mobile communication receivers, the channel is estimated based on pilot symbols to allow for a coherent detection and decoding in a separate processing step. Currently, much work is spent on receivers which break up this separation, e.g., by enhancing channel estimation based on reliability information on the data symbols. In this paper, we evaluate the possible gain of a joint processing of data and pilot symbols in comparison to the case of a separate processing in the context of stationary Rayleigh flat-fading channels. Therefore, we discuss the nature of the possible gain of a joint processing of pilot and data symbols. We show that the additional information that can be gained by a joint processing is captured in the temporal correlation of the channel estimation error of the solely pilot-based channel estimation, which is not retrieved by the channel decoder in case of separate processing. In addition, we derive a new lower bound on the achievable rate for joint processing of pilot and data symbols. Finally, the results are extended to multiple-input multiple-output channels.

PCA Application in Channel Estimation in MIMO-OFDM System

Initial estimation is a considerable issue in channel estimation techniques, since all of the following processes depends on it, which in this paper its improvement is discussed. Least Square (LS) method is a common simple way to estimate a channel initially but its efficiency is not as significant as more complex approaches. It is possible to enhance channel estimation performance by using some methods such as principal component analysis (PCA), which is not prevalent in channel estimation, and its adaptation to channel information can be challenging. PCA method improves initial estimation performance by projecting data onto direction of eigenvectors by means of using simple algebra. In this paper, channel estimation is examined in Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system, with significant advantages such as an acceptable performance in frequency selective fading channel. Moreover the proposed channel estimation method manipulates the benefits of MIMO channel by using the information, gained by all channels to estimate the information of each receiver.

Channel Estimation and LDPC Code Puncturing Schemes Based on Incremental Pilots for OFDM

In this letter, we propose a channel estimation algorithm based on incremental pilots. These are pilots additionally inserted after puncturing the modulated orthogonal frequency division multiplexing (OFDM) symbols to enhance channel estimation performance without lowering bandwidth efficiency. A low-density parity-check code puncturing scheme is also proposed to prevent the performance degradation due to the codeword bit loss caused by punctured OFDM symbols.

Optimal training design and placement for MIMO orthogonal frequency division multiplexing channel estimation

This paper deals with optimal training design and placement over multiple orthogonal frequency division multiplexing (OFDM) symbols for the least squares (LS) channel estimation in multiple-input multipleoutput (MIMO) OFDM systems. First, the optimal pilot sequences over multiple OFDM symbols are derived by co-cyclic Jacket matrices based on the minimum mean square error (MSE) of the LS channel estimation. Then, an enhanced channel estimation method using sliding window is proposed to improve further the performance for the optimal pilot sequences in fast-varying channels. Simulation results show that the enhanced method can efficiently improve the performances for the optimal pilot sequences over two and four OFDM symbols, especially in fast-varying channels.

Enhanced channel estimation and symbol detection for high speed multi-input multi-output underwater acoustic communications

The need for achieving higher data rates in underwater acoustic communications leverages the use of multi-input multi-output (MIMO) schemes. In this paper two key issues regarding the design of a MIMO communications system, namely, channel estimation and symbol detection, are addressed. To enhance channel estimation performance, a cyclic approach for designing training sequences and a channel estimation algorithm called the iterative adaptive approach (IAA) are presented. Sparse channel estimates can be obtained by combining IAA with the Bayesian information criterion (BIC). Moreover, the RELAX algorithm can be used to improve the IAA with BIC estimates further. Regarding symbol detection, a minimum mean-squared error based detection scheme, called RELAX-BLAST, which is a combination of vertical Bell Labs layered space-time (V-BLAST) algorithm and the cyclic principle of the RELAX algorithm, is presented and it is shown that RELAX-BLAST outperforms V-BLAST. Both simulated and experimental results are provided to validate the proposed MIMO scheme. RACE'08 experimental results employing a 4 x 24 MIMO system show that the proposed scheme enjoys an average uncoded bit error rate of 0.38% at a payload data rate of 31.25 kbps and an average coded bit error rate of 0% at a payload data rate of 15.63 kbps.

Enhanced Channel Estimation Using Superimposed Training Based on Universal Basis Expansion

In this correspondence, an approach to enhance the quality of superimposed training (ST) based channel estimation procedures is proposed. The approach is based on postprocessing the estimated channel. This postprocessing is performed with the projection of the estimated channel onto a set of orthogonal functions known as the Universal Basis (UB), that were defined in [A. G. Orozco-Lugo, R. Parra-Michel, D. McLernon, and V. Kontorovitch, ldquoEnhancing the Performance of the CR Blind Channel Estimation Algorithm Using the Karhunen-Loeve Expansion,rdquo Proceedings of the ICASSP, May 2002, pp. III-2653-III-2656 ]. The projection leads to improved channel estimation when compared to raw ST methods. We demonstrate the enhanced performance of the proposed technique by means of both theoretical formulas and simulation results, focusing on data dependent ST.

Joint Channel and DOA Estimation for Multicarrier CDMA Uplink Transmissions

The use of antenna arrays in wireless communications makes it possible to estimate the directions of arrival (DOAs) of impinging waveforms. The latter can be exploited to enhance channel estimation accuracy or as an input for advanced mobile positioning systems. In this paper, we consider the uplink of a multicarrier code-division multiple-access (MC-CDMA) network in which the base station is endowed with multiple receiving antennas arranged in a uniform linear array. Transmission takes place over a multipath channel, and the goal is the joint estimation of the channel responses and DOAs of the uplink signals. In doing so, we follow a maximum-likelihood (ML) approach and assume that users transmit orthogonal training sequences to facilitate the task of separating the signals. This way, all unknown parameters are estimated independently of each other with affordable complexity. Theoretical analysis and computer simulations are used to assess the performance of the proposed scheme and make comparisons with existing alternatives.

Enhancing Channel Estimation in Cognitive Radio Systems by means of Bayesian Networks

This paper proposes enhancements to the channel(-state) estimation phase of a cognitive radio system. Cognitive radio devices have the ability to dynamically select their operating configurations, based on environment aspects, goals, profiles, preferences etc. The proposed method aims at evaluating the various candidate configurations that a cognitive transmitter may operate in, by associating a capability e.g., achievable bit-rate, with each of these configurations. It takes into account calculations of channel capacity provided by channel-state estimation information (CSI) and the sensed environment, and at the same time increases the certainty about the configuration evaluations by considering past experience and knowledge through the use of Bayesian networks. Results from comprehensive scenarios show the impact of our method on the behaviour of cognitive radio systems, whereas potential application and future work are identified.