Phase rotation for constructing uniform frequency spectrum in IFDMA communication

The acquisition of accurate channel estimation is important for Orthogonal Frequency-Division Multiplexing (OFDM) system to reliably recover the transmitted data symbols. Decision directed channel estimation (DDCE) has been utilized to improve the accuracy of conventional training-based channel estimation. However, this method can only provide limited improvement when the data decision feedback comprises a large portion of decision errors at low signal-to-noise (SNR) range. A new Iterative DDCE (IDDCE) scheme with reliable data feedback selection is proposed in this paper. The unreliable data decisions are eliminated on the subcarriers where noise components are enhanced due to the impact of frequency selective channel. An explicit expression of the variance of channel estimation error is derived, based on which the optimal selection criteria are also derived to minimize the variance. Simulation results show that the accuracy of channel estimation is significantly improved with the proposed algorithm.

The Channel estimation in Vehicle-to-Vehicle (V2V) communications is critical due to the time-varying characteristics of the V2V channel. Hence, the authors propose a hybrid approach towards channel estimation by combining Pilot Symbol Aided Channel Estimation (PSACE), Improved Crow Search Algorithm (ICSA), and Decision Directed Channel Estimation (DDCE) by employing Weight Regularized Convolutional Neural Network (WCNN). Hybrid channel estimation by combining the properties of PSACE and DDCE. PSACE suffers from pilot overhead issue due to the demand of huge number of pilots for channel estimation. On the other hand, DDCE suffers from error propagation in fast fading environments. The proposed system employs an ICSA and WCNN to overcome the issues faced by channel estimation methods. Further, the proposed strategy replaces the analytical modeling of the channel with the help of the neural network. Optimized pilots obtained from ICSA along with data symbols are fed to WCNN to estimate the channel in a non-stationary environment. Finally, the performance of the proposed method is evaluated in terms of Bit Error Rate, Mean Square Error, and Packet Error Rate and the simulations are carried out under various V2V scenarios for testing its sturdiness.

This paper proposes the theoretical derivation method of both the frequency spectrum and the bit error rate (BER) performance for uplink Orthogonal Frequency Division Multiple Access (OFDMA) in the presence of the nonlinear distortion. Since OFDMA has two different subcarrier allocation methods such as localized FDMA (LFDMA) and interleaved FDMA (IFDMA), there is the difference, in terms of the influence of the nonlinear distortion at each mobile station (MS) on the out-band radiation and the BER degradation, between LFDMA and IFDMA. Therefore, it is meaningful to clarify this difference by means of the theoretical approach. The feature of the proposed approach is to represent both the frequency spectrum and the BER performance by the simple series form formula, which enables us to overview these performances without any time-consuming computer simulations. The validity of the proposed formula is confirmed by the agreement with the computer simulation results with the parameters of the number of MSs and the input back-off (IBO).

A decision-directed (DD) channel estimation based on iterative linear minimum mean square error (LMMSE) is proposed for orthogonal frequency division multiplexing systems. Existing DD channel estimation is well known to have the problem of error propagation because of symbol-by-symbol detection. The proposed algorithm can estimate the correction term of current channel state information (CSI) according to the error vector of previous CSI by applying the orthogonality principle, and corrects the current CSI with this correction term. Analysis and simulation results have shown that this method has no error propagation problem. The performance of the proposed algorithm is much better than the conventional DD channel estimation, and close to the optimal LMMSE estimator, but with much less computational complexity compared with the optimal LMMSE estimator.

The authors describe a robust channel prediction technique for a direct sequence spread spectrum (DS-SS) system in a fast fading environment. For improved performance the RAKE filter taps are coherently combined, hence accurate channel estimation is required. An FIR type linear prediction filter for each RAKE filter tap is used to estimate the channel response. In order to do this, the data decisions are fed back to the prediction filter. The stability of the proposed system is achieved through differential encoding of the data bits. It is demonstrated through simulations that the performance of the proposed decision directed receiver is better than that of an idealised receiver where channel estimation is not corrupted by decision feedback errors (e.g. by means of employing a pilot signal). The channel estimate can be significantly improved by employing a second stage channel estimation filter.

The DVB-T2 standard is widely used in recent years, which is based on orthogonal frequency division multiplexing (OFDM) systems. In OFDM system, frequency-domain pilots are usually employed to perform channel estimation. To reduce the number of pilots and hence improve spectral efficiency, decision-directed channel estimation (DDCE) has been considered in the new DVB-T2 standard. In this paper we will address the noise amplification problem of DDCE in DVB-T2 systems. We propose to employ the weighted least-squares method to improve the performance of DDCE in DVB-T2 systems. Simulation results show that the proposed scheme considerably improves the mean-squared estimation errors as compared with existing algorithms in [2,3].

In this paper, we evaluate the computational complexity and the performance of the RAKE receivers for the Direct Sequence---Ultra Wideband (DS-UWB) with considering the accuracy of channel estimation in a multipath channel. As RAKE receivers for DS-UWB, we consider the maximal-ratio combining (MRC)-RAKE, the minimum mean square error (MMSE)-RAKE, and the MRC-RAKE-Equalizer that is the MRC-RAKE followed by a liner equalizer. Generally, if the channel estimation is perfect, as the number of fingers or taps increases, the performance of each receiver is improved, however the computational complexity of each receiver increases. In practice, the channel estimation is not perfect. The channel estimation error makes their performances degraded. Therefore, the performances of the RAKE receivers depend on the accuracy of channel estimation. Consequently, we evaluate the computational complexities and the Bit Error Rates (BERs) of MRC-RAKE, MMSE-RAKE, and MRC-RAKE-Equalizer with considering the accuracy of channel estimation for DS-UWB. We show that the accuracy of channel estimation affects the BER of each receiver significantly. We also show that when the accuracy of channel estimation is high, MRC-RAKE-Equalizer can achieve the better BER than MMSE-RAKE with less computational complexity, while MMSE-RAKE can achieve the better BER than MRC-RAKE-Equalizer when the accuracy of channel estimation is low.

An iterative receiver, proposed in our previous works, employs decision directed phase noise compensation (DD-PNC) and decision directed channel estimation (DDCE), and thus can effectively reduce the effects of phase noise on millimeter-wave (mm-wave) orthogonal frequency division multiplexing (OFDM) systems. When the iterative receiver is applied to mm-wave communications between fixed points and high speed trains (HSTs), not only phase noise but also Doppler shift should be considered. In this paper, we evaluate the iterative DD-PNC and DDCE scheme in the HST environment by using a dynamic multipath channel model. Computer simulations show that the proposed scheme can reduce not only the effects of phase noise but also that of Doppler shift, when angle spread (AS) is small. However, when AS becomes larger, it is demonstrated that the performance of the proposed scheme degrades. For alleviating the degradation, we modify DDCE into a symbol by symbol manner, symbol-DDCE (SDDCE) that improves the performance remarkably.

Transportation infrastructures integrate advanced Information Technology to enable the operations and management of transportation systems. Advanced vehicle and road systems of a comprehensive concept that improve the efficiency and safety of road traffic are being built and will be commercially available through Intelligent Transport Systems (ITS) technology and services. To support ITS technology, Vehicle-To-Everything (V2X) is needed, and in the 3rd Generation Partnership Project, many studies have focused on Long Term Evolution (LTE)-based vehicle communications. In order to realize reliable and optimized communications performance in vehicle communications, which move in propagation environments at high speed, in this study, we propose a novel channel estimation scheme suited for LTE sidelink-based Vehicle-To-Vehicle systems. Conventional channel estimation schemes can be categorized as Decision-Directed Channel Estimation, spectral temporal averaging, and smoothing methods. In this study, unlike conventional channel estimation schemes, we propose a Novel Interference Cancellation of Channel Estimation (NICCE) using Quadratic Smoothing of the pilot symbols, which estimates a channel with greater accuracy, and a novel interference cancellation of channel estimation in data symbols. In simulation results, the proposed NICCE scheme shows improved overall performance in terms of the Normalized Mean Square Error and uncoded Bit Error Rate relative to conventional schemes.

Single-carrier (SC) transmission using frequency-domain space-time block coded joint transmit/receive diversity (FD-STBC-JTRD) combined with transmit frequency-domain equalization (FDE) obtains full spatial diversity gain and frequency diversity gain. Recently, we derived the optimal transmit frequency-domain equalization (FDE) for SC FD-STBC-JTRD and showed that the optimal transmit FDE, which uses multiple weight matrices corresponding to multiple coded blocks in a STBC code-word, achieves the received signal-to-interference plus noise power ratio (SINR) 1/RSTBC times higher than the conventional transmit FDE which uses the single weight matrix over a STBC code-word, where RSTBC denotes the STBC code rate. However, our past study of SC FD-STBC-JTRD with the optimal transmit FDE assumed ideal channel estimation. In this paper, we provide theoretical analysis of the received SINR and the conditional bit error rate (BER) of SC FD-STBC JTRD with cyclic delay pilot channel estimation (CDP-CE) and discuss the impact of channel estimation error. Then, we evaluate, by computer simulation, the average BER performance when using SC FD-STBC-JTRD with the optimal transmit FDE and show that the optimal transmit FDE can achieve the received SINR 1/RSTBC times higher than the conventional transmit FDE even in the presence of the channel estimation error.

The detection performance of coherent OFDM receiver significantly depends on the accuracy of channel estimation. The accuracy of channel estimation can be improved by properly post-processing the channel estimate using a so called channel estimation filter (CEF). Linear minimum mean-squared error (MMSE) filter is optimum as the CEF, but it may not practical due to implementation complexity. We consider the use of a reduced-complexity CEF whose tap coefficient is real valued and symmetrically weighted (RSW). The optimum RSW CEF is analytically designed using the multi-path intensity profile and SNR of the channel. We also propose a method to adapt the coefficient of the RSW CEF to the channel condition. Numerical results show that the proposed RSW CEF can provide channel estimation performance comparable to that of a linear MMSE filter, while significantly reducing the computational complexity. In addition, the proposed RSW CEF can provide performance robust to unknown timing offset with a fractional dB loss compared to the optimum one.

In this paper, we present a unified mathematical framework to analyze the bit-error rate (BER) performance of general linear coherent multiuser receivers with diversity reception and imperfect channel estimation for doubly selective Rician-fading asynchronous code-division multiple-access channels. BERs of linear receivers with channel state information and data-aided channel estimation are analyzed, and both exact and low-complexity approximate BER evaluation formulas are presented. Furthermore, by using a Markov chain steady-state analysis, a tight BER approximation for receivers with decision-directed channel estimation is proposed. Numerical and simulation results verify the accuracy of the proposed BER evaluation methods.

Channel estimation is one of the most important aspects of wireless communication. Especially in Sparse Code Multiple Access (SCMA) system, the accuracy of channel estimation has a significant impact on decoding performance. Various methods, so far, have been developed for channel estimation. Most of these methods regard channel estimation as a parameter estimation problem of linear models. However, these methods require lots of time-frequency resources to ensure high estimation accuracy. In massive connection scenarios, high pilot overhead makes the spectrum resource more scarce. Therefore, the drawback of conventional channel estimation methods limits the further improvement of system capacity in the Internet of Things(IoT) when time-frequency resources is restricted. To address this problem, in this paper, we propose an efficient channel estimation scheme and sparse pilot structure design method in SCMA system based on complex-valued sparse autoencoder which is effective to learn features of wireless channel. Complex-valued sparse autoencoder is a kind of neural network with complex-valued weights. It contains two parts: encoder and decoder. In our work, the encoder part is used to realize pilot design. Channel estimation is implemented by the decoder. Complex-valued weights obtained from training are used as baseband pilots. Compared with maximum likelihood channel estimation (MLE) of linear model, the proposed method can achieve higher channel estimation accuracy with more sparse pilot structure. The bit-error rates performance of the SCMA receiver in our work is very close to that of the perfect channel state information (CSI).

In this paper, to improve the performance of PB/MC-CDMA system, we have researched about the decision feedback channel estimation method using the pilot symbol with data symbol. The PB/MC-CDMA system is able to obtain the improved BER by frequency diversity gain and frequency domain equalizer in the frequency selective fading channel. However, when it is not the estimating of channel exactly, it is degrading the performance of BER in the system for occurred the interference among users. To improve the performane system in the multi-user environment the proposed system is using the decision feedback to estimate channel using the channel estimated value of the first stage and second stage. The proposed system is evaluated by computer simulation. The proposed system is not only able to improve the performance of BER by decreasing the interference to each user, but also the proposed system is possible to reduce number of pilot symbol to estimate the channel. Therefore, it confirmed the proposed system improves the performance than the conventional system.

Orthogonal frequency-division multiplexing (OFDM) is resistant to frequency selective fading due to the longer symbol duration. However, mobile applications channel timing fluctuations in one OFDM signal cause intercarrier-interference (ICI), which reduces performance. This research presented the support vector regression (SVR) model-based channel estimation technique for coherent optical communication systems. Due to the coherent optical orthogonal frequency-division-multiplexed (COOFDM) system, a channel model is developed that includes linear fibre dispersion effects, noise from optical amplifiers, and inter-carrier interference generated by laser phase noise. As a result, for such a system, an accurate channel estimate is essential. Based on this concept, derivation of channel estimation and phase estimation for the system of CO-OFDM. The proposed method is tested and evaluated using MATLAB software. Computer simulation results for several standard methods such as extreme learning machines (ELM) and artificial neural networks (ANN) validate the feasibility of the suggested methodology. The CO-OFDM system’s transmission experiments and computer simulations prove that the support vector machine-based model following pilot-assisted phase estimation gives the optimal performance. Therefore, results depicted that the channel estimation utilizing the SVR model gives good performance than the other methods, thus the proposed model gives an accurate CE process, respectively.