Pilot-aided Channel Estimation Research Articles

On the Pilot-Aided Channel Estimation for Windowed OTFS With Data Interference in Rapidly Time-Varying Channels

On the Pilot-Aided Channel Estimation for Windowed OTFS With Data Interference in Rapidly Time-Varying Channels

Confidential multiple-input multiple-output optical camera communication aided by a two-dimensional pilot.

Optical camera communication (OCC) has attracted increased attention for its inherent security advantage. However, there still exists the risk of eavesdropping on the broadcasting channel of OCC. To achieve confidential communication, we propose the confidentiality-interference dual light-emitting diode (LED) communication (CIDLC) scheme at the transmitter (TX) and elimination of interference (EI) scheme at the receiver (RX). Meanwhile, interference signals refer to the bit shift of confidential signals. Further, we propose the two-dimensional pilot-aided channel estimation (2D-PACE) scheme to enhance the reliability of multiple-input multiple-output (MIMO) OCC. Experiment results validate the effectiveness of our schemes, which guarantee confidentiality while performing well at a 2 m non-line-of-sight (NLOS) distance. Finally, the communication-illumination integration OCC is constructed via the energy equalization coding (EEC) scheme.

Affine Frequency Division Multiplexing for Next Generation Wireless Communications

Affine Frequency Division Multiplexing (AFDM), a new chirp-based multicarrier waveform for high mobility communications, is introduced here. AFDM is based on discrete affine Fourier transform (DAFT), a generalization of discrete Fourier transform, which is characterized by two parameters that can be adapted based on the Doppler spread of doubly dispersive channels. First, we derive the explicit input-output relation in the DAFT domain showing the effect of AFDM parameters in the input-output relation. Second, we show how the DAFT parameters underlying AFDM have to be set so that the resulting DAFT domain impulse response conveys a full delay-Doppler representation of the channel. Then, we show analytically that AFDM can achieve the optimal diversity order in doubly dispersive channels, where optimal diversity order refers to the number of multipath components separable in either the delay or the Doppler domain, due to its full delay-Doppler representation. Furthermore, we present a low complexity detection method taking advantage of zero-padding. We also propose an embedded pilot-aided channel estimation scheme for AFDM, in which both channel estimation and data detection are performed within the same AFDM frame. Finally, simulations corroborate the validity of our analytical results and show the significant performance gains of AFDM over state-of-the-art multicarrier schemes in high mobility scenarios.

Reliability performance analysis for OTFS modulation based integrated sensing and communication

In this paper, we develop an orthogonal time frequency space (OTFS) modulation based integrated (radar) sensing and communication (ISAC) technique, namely OTFS-ISAC, for the high mobility multiuser system. In particular, at the transmitter, it can alternate the modes between sensing and communication using time division multiplexing so that it takes advantage of radar assistance to design the OTFS frame structure for reducing the overhead of guard symbols. At the receiver, based on the embedded pilot-aided channel estimation, it employs zero-forcing (ZF) equalization. For performance analysis, we derive the error probability of channel estimation based on radar sensing, and find the outage probability of downlink communication. Then, we introduce an adaptive power allocation scheme at the transmitter to optimize the outage probability of the communication link. Our simulations show that, by properly selecting N, M, and the pilot symbol strength, the proposed OTFS-ISAC scheme can reduce the overhead of guard symbols while achieving promising reliability performance of the downlink transmission with relative low channel estimation error.

Indexed-channel estimation under frequency and time-selective fading channels in high-mobility systems

<p><span lang="EN-US">Index modulation (IM) techniques have been employed in different communication systems to improve bandwidth efficiency by carrying additional information bits. In high-mobility communication systems and under both time-selective and frequency-selective fading channels with Doppler spread, channel variations can be tracked by employing pilot-aided channel estimation with minimum mean-squared error estimation. However, inserting pilot symbols among information symbols reduces the system's spectral efficiency in pilot-aided channel estimation schemes. We propose pilot-aided channel estimation with zero-pilot symbols and an energy detection scheme to tackle this issue. Part of the information bit-stream is conveyed by the indices of zero-pilot symbols leading to an increase in the system's spectral efficiency. We used an energy detector at the receiver to detect the transmitted zero-pilot symbols. This paper examines the impacts of diversity order on the zero-pilot symbol detection error probability and the mean-squared of error estimation. The impacts of pilot symbols number and the zero-pilot symbol number on the mean-squared error of the minimum mean-squared error (MMSE) estimator and the system error performance are also investigated in this paper.</span></p>

Performance of STBC Based MIMO-OFDM Using Pilot-aided Channel Estimation

Many studies have been published to address the growing issues in wireless communication systems. Space-Time Block Coding (STBC) is an effective and practical MIMO-OFDM application that can address such issues. It is a powerful tool for increasing wireless performance by coding data symbols and transmitting diversity using several antennas. The most significant challenge is to recover the transmitted signal through a time-varying multipath fading channel and obtain a precise channel estimation to recover the transmitted information symbols. This work considers different pilot patterns for channel estimation and equalization in MIMO-OFDM systems. The pilot patterns fall under two general types: comb and block types, with a proper arrangement suitable to the multiple transmit antennas. The two main channel estimation methods, LS and MMSE, are compared by evaluating performance in terms of Bit Error Rate (BER) to analyze the performance of pilot-aided channel estimation for 2x2 and 4x4 MIMO arrangements utilizing LTE parameters and the effects of modifying different numbers of OFDM subcarriers under different channel models It has been discussed, a 4x4 system performs better than a 2x2 system in terms of BER with an acceptable amount of additional complexity.

Low PAPR channel estimation for OTFS with scattered superimposed pilots

Orthogonal time frequency space (OTFS) modulation has been proven to be superior to traditional orthogonal frequency division multiplexing (OFDM) systems in high-speed communication scenarios. However, the existing channel estimation schemes may results in poor peak to average power ratio (PAPR) performance of OTFS system or low spectrum efficiency. Hence, in this paper, we propose a low PAPR channel estimation scheme with high spectrum efficiency. Specifically, we design a multiple scattered pilot pattern, where multiple low power pilot symbols are superimposed with data symbols in delay-Doppler domain. Furthermore, we propose the placement rules for pilot symbols, which can guarantee the low PAPR. Moreover, the data aided iterative channel estimation was invoked, where joint channel estimation is proposed by exploiting multiple independent received signals instead of only one received signal in the existing scheme, which can mitigate the interference imposed by data symbols for channel estimation. Simulation results shows that the proposed multiple scattered pilot aided channel estimation scheme can significantly reduce the PAPR while keeping the high spectrum efficiency.

Noncoherent OFDM Transmission via Off-the-Grid Joint Channel and Data Estimation

Pilot-aided channel estimation techniques are known to waste the spectral bandwidth. An off-the-grid blind estimator for time-variant orthogonal frequency division multiplexing (OFDM) systems is studied in this letter. In this regard, we propose a blind estimator based on atomic norm minimization (ANM) for OFDM systems. To do so, at the first transmission block, using a lifted ANM (LANM) and simple constraint on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula> norm of data, we simultaneously estimate the channel and data. For the subsequent blocks, we use a penalized ANM (PANM) to simultaneously track the channel’s parameters and detect transmit signals. The proposed problems require an infinite dimensional search, hence are NP-hard. Therefore, we propose two semidefinite programs (SDPs) to implement them. We then derive the total computational complexity of the proposed estimator. The simulation results show the superiority of the proposed estimator to the state-of-the-arts.

3D indoor positioning with spatial modulation for visible light communications

In this paper, a novel three-dimensional (3D) indoor visible light positioning (VLP) algorithm is proposed based on the spatial modulation (SM) and its error performance assessed as compared to the conventional received signal strength (RSS)-based 3D VLP systems. As contrasted to the traditional VLP system, the proposed SM-based 3D VLP system first estimates the optical channel gain between the transmitting light-emitting diodes (LEDs) and the two photo detectors (PDs) attached to the user by a pilot-based channel estimation technique. Then, unknown 3D positions of the receiver are determined by the trilateration algorithm with distances computed from the estimates of the channel gains. Consequently, the 3D VLP system achieves an interference-free transmission with increased spectral efficiency and without the need for a demultiplexing process at the receiving end. The algorithm’s performance is evaluated regarding positioning error by applying the SM over four LEDs and the number of pilots selected as a function of the environmental signal-to-noise ratios (SNRs). The computer simulation results show that the positioning errors are obtained in an order of magnitude smaller than RSS-based techniques in an indoor industrial environment. This is mainly because the distances involved in determining the 3D positions can be determined more precisely by the pilot-aided channel estimation method without creating any data rate problem in transmission due to the higher spectral efficiency of the SM.

QoS-Aware Resource Allocation with Pilot-Aided Channel Estimation for Heterogeneous Wireless Networks

The deployment of heterogeneous networks (HetNets) is a way to increase the network capacity and release part of the traffic generated by users inside a cell to small-scale wireless networks for service. In this context, the main problem is managing the interference due to the coexistence of small cells and macro cells. In this paper, a QoS-aware Resource Allocation (RA) algorithm jointly working with admission control (AC) over a two-tier HetNet scenario is investigated in the presence of both the pilot-symbols for channel estimation and the channel estimation error. The RA algorithm allows two users, the macro cell user (CU) and small cell user (SU), to simultaneously share the same resource block. Moreover, system performance and fairness are improved by including adaptive power allocation to users over resource blocks. In the framework of RA with proportional rate constraints, a novel algorithm is designed by including the effects of pilot-aided channel estimation. The algorithm is able to distribute the same proportional rate to all CUs and SUs, even in the presence of channel estimation error. Relevant numerical results for the downlink of a two-tier HetNet with pilot-aided channel estimation show that the rate dispersion is driven to zero while the sum-rate is maximized, and the average user rate penalty with respect to a perfect-CSI scenario may rise to 20%.

Low-Resolution Precoding for Multi-Antenna Downlink Channels and OFDM.

Downlink precoding is considered for multi-path multi-input single-output channels where the base station uses orthogonal frequency-division multiplexing and low-resolution signaling. A quantized coordinate minimization (QCM) algorithm is proposed and its performance is compared to other precoding algorithms including squared infinity-norm relaxation (SQUID), multi-antenna greedy iterative quantization (MAGIQ), and maximum safety margin precoding. MAGIQ and QCM achieve the highest information rates and QCM has the lowest complexity measured in the number of multiplications. The information rates are computed for pilot-aided channel estimation and a blind detector that performs joint data and channel estimation. Bit error rates for a 5G low-density parity-check code confirm the information-theoretic calculations. Simulations with imperfect channel knowledge at the transmitter show that the performance of QCM and SQUID degrades in a similar fashion as zero-forcing precoding with high resolution quantizers.

Pilot Symbol Aided Channel Estimation for OCDM Transmissions

Pilot-aided channel estimation allows the receiver to acquire channel state information (CSI) for each multicarrier block by multiplexing data and pilot symbols in the same block, as long as they can be decoupled. This work proposes several frequency-domain pilot multiplexing techniques to enable independent channel estimation and detection at the receiver for orthogonal chirp division multiplexing (OCDM) transmissions in frequency-selective channels. Analysis shows that each of the proposed schemes is able to achieve the mean squared error (MSE) lower bound for channel estimation and has greater spectral efficiency than the existing schemes for OCDM and chirp spread orthogonal frequency division multiplexing (OFDM).

Improved Atomic Norm Based Time-Varying Multipath Channel Estimation

In this paper, improved channel gain delay estimation strategies are investigated when practical pulse shapes with finite block length and transmission bandwidth are employed. Pilot-aided channel estimation with an augmented atomic norm based approach is proposed to promote the low rank structure of the time-varying narrowband leaked channel. All the channel parameters, i.e., delays, Doppler shifts, and channel gains are recovered. Design choices which ensure unique estimates of channel parameters for rectangular, Gaussian, and root-raised-cosine pulse shapes are examined in the noiseless case, respectively. Furthermore, a perturbation analysis is conducted to measure the impact of noise and further design choices for parameters are proposed to mitigate the effects of noise. Finally, numerical results verify the theoretical analysis and show performance improvements over the previously proposed method.

Pilot-Aided Channel Estimation for Massive MIMO Systems in TDD-mode Using Walsh-Hadamard Transformed Subsampled Data at the Base Station

Massive MIMO has been adopted for 5G communications due to its wide spectrum and energy efficiency. To realize its potential performance, however, accurate channel state information is essential. Here we propose a subsampling algorithm based on the Walsh-Hadamard transform (WHT) to perform channel propagation coefficient matrix estimation of a massive MIMO communication system operating in time division duplexing (TDD) mode. To do so, we apply an iterative graph-based Hadamard transform algorithm to compute the channel propagation coefficient matrix. To evaluate algorithm performance, we implement it in a seven cell scenario where the mobile users in the cell of interest are assigned the same set of orthogonal Walsh-Hadamard (WH) pilot sequences as the mobile users in the other cells and assume the worst-case scenario when all mobile users in all cells transmit their pilot sequences at the same time. Simulation results show that the proposed algorithm can accurately estimate the channel propagation coefficients with lower computational complexity than the commonly used least square (LS) estimation approach.

Channel Estimation Based on Deep Learning in Vehicle-to-Everything Environments

Channel estimation in vehicle-to-everything (V2X) communications is a challenging issue due to the fast time-varying and non-stationary characteristics of wireless channel. To grasp the complicated variations of channel with limited number of pilots in the IEEE 802.11p systems, data pilot-aided (DPA) channel estimation has been widely studied. However, the error propagation in the DPA procedure, caused by the noise and the channel variation within adjacent symbols, limits the performance seriously. In this letter, we propose a deep learning based channel estimation scheme, which exploits a long short-term memory network followed by a multilayer perceptron network to solve the error propagation issue. Simulation results show that the proposed scheme outperforms currently widely-used DPA schemes for the IEEE 802.11p-based V2X communications.

A novel delay dictionary design for compressive sensing-based time varying channel estimation in OFDM systems

Compressive sensing (CS) is a new attractive technique adopted for Linear Time Varying channel estimation. orthogonal frequency division multiplexing (OFDM) was proposed to be used in 4G and 5G which supports high data rate requirements. Different pilot aided channel estimation techniques were proposed to better track the channel conditions, which consumes bandwidth, thus, considerable data rate reduced. In order to estimate the channel with minimum number of pilots, compressive sensing CS was proposed to efficiently estimate the channel variations. In this paper, a novel delay dictionary-based CS was designed and simulated to estimate the linear time varying (LTV) channel. The proposed dictionary shows the suitability of estimating the channel impulse response (CIR) with low to moderate Doppler frequency shifts with acceptable bit error rate (BER) performance.

Pilot and Data Power Allocation in Poisson Interference Field With Protected Zone for Physical-Layer Security

Physical-layer security has become widely recognized as a promising technique to enhance wireless security by exploiting the characteristics including fading, noise, and interference. This letter explores an opportunity to enhance physical-layer security by balancing the power expense between pilot and payload signals without any prior knowledge related to eavesdroppers. In lieu of presuming perfect channel acquisition, we consider a practical wiretap channel with the receivers enabled by pilot-aided channel estimation (CE). The problem is tackled by accounting for the network interference from cochannel interferers in unknown locations by which the secrecy level is significantly affected. Specifically, the secrecy transmission rate (STR) reflecting the CE errors is derived for the worst-case within the use of a protected zone. We investigate the feasible region of pilot and data power allocation under reliability and secrecy constraints, and the optimal power allocation for pilot and data to maximize the STR is proposed, whose performance is verified via simulations.

Nearest Neighbor Decoding and Pilot-Aided Channel Estimation for Fading Channels.

We study the information rates of noncoherent, stationary, Gaussian, and multiple-input multiple-output (MIMO) flat-fading channels that are achievable with nearest neighbor decoding and pilot-aided channel estimation. In particular, we investigate the behavior of these achievable rates in the limit as the signal-to-noise ratio (SNR) tends to infinity by analyzing the capacity pre-log, which is defined as the limiting ratio of the capacity to the logarithm of the SNR as the SNR tends to infinity. We demonstrate that a scheme estimating the channel using pilot symbols and detecting the message using nearest neighbor decoding (while assuming that the channel estimation is perfect) essentially achieves the capacity pre-log of noncoherent multiple-input single-output flat-fading channels, and it essentially achieves the best so far known lower bound on the capacity pre-log of noncoherent MIMO flat-fading channels. Extending the analysis to fading multiple-access channels reveals interesting relationships between the number of antennas and Doppler bandwidth in the comparative performance of joint transmission and time division multiple-access.

Projection wavelet weighted twin support vector regression for OFDM system channel estimation

In this paper, an efficient projection wavelet weighted twin support vector regression (PWWTSVR) based orthogonal frequency division multiplexing system (OFDM) system channel estimation algorithm is proposed. Most Channel estimation algorithms for OFDM systems are based on the linear assumption of channel model. In the proposed algorithm, the OFDM system channel is consumed to be nonlinear and fading in both time and frequency domains. The PWWTSVR utilizes pilot signals to estimate response of nonlinear wireless channel, which is the main work area of SVR. Projection axis in optimal objective function of PWWRSVR is sought to minimize the variance of the projected points due to the utilization of a priori information of training data. Different from traditional support vector regression algorithm, training samples in different positions in the proposed PWWTSVR model are given different penalty weights determined by the wavelet transform. The weights are applied to both the quadratic empirical risk term and the first-degree empirical risk term to reduce the influence of outliers. The final regressor can avoid the overfitting problem to a certain extent and yield great generalization ability for channel estimation. The results of numerical experiments show that the propose algorithm has better performance compared to the conventional pilot-aided channel estimation methods.

BEM-PSP for Single-Carrier and SC-FDMA Communication Over a Doubly Selective Fading Channel

In this paper, we consider pilot-aided channel estimation and equalization for single-carrier and single-carrier frequency division multiple-access (SC-FDMA) transmission over doubly-selective channels (DSC). To reduce the channel estimation (CE) parameters, the DSC is modelled using a complex-exponential basis expansion model (CX-BEM) with non-uniform BEM frequencies. We optimize the CX-BEM basis functions using CE error minimization as the objective. As a result, the channel modelling error is greatly reduced. Next, we propose a BEM-based per-survivor processing (PSP) technique and combine it with a decision-directed channel estimator to obtain a channel-tracking equalizer at the receiver. The resultant BEM-PSP receiver significantly improves the channel estimation mean square error (MSE) and the bit error rates (BER) performance in fast fading multi-path channel, thanks to the channel tracking capability embedded within its Viterbi equalizer. Finally, we employ cross-frame channel interpolation, and power distribution between the data and pilot symbols to further improve the system performance at high fading rates. Extensive simulation results show that our BEM-PSP receiver outperforms many existing methods and approaches close to an ideal receiver with perfectly known CSI under various fading scenarios.