Least Square Channel Estimation Algorithm Research Articles

Artificial Intelligence-Aided Receiver for a CP-Free OFDM System: Design, Simulation, and Experimental Test

Orthogonal frequency division multiplexing (OFDM), usually with sufficient cyclic prefix (CP), has been widely applied in various communication systems. The CP in OFDM consumes additional resource and reduces spectrum and energy efficiency. However, channel estimation and signal detection are very challenging for CP-free OFDM systems. In this paper, we propose a novel artificial intelligence (AI)-aided receiver (AI receiver) for a CP-free OFDM system. The AI receiver includes a channel estimation neural network (CE-NET) and a signal detection neural network based on orthogonal approximate message passing (OAMP), called OAMP-NET. The CE-NET is initialized by the least-square channel estimation algorithm and refined by a linear minimum mean-squared error neural network. The OAMP-NET is established by unfolding the iterative OAMP algorithm and adding several trainable parameters to improve the detection performance. We first investigate their performance under different channel models through extensive simulation and then establish a real transmission system using a 5G rapid prototyping system for an over-the-air (OTA) test. Based on our study, the AI receiver can estimate time-varying channels with a single training phase. It also has great robustness to various imperfections and has better performance than those competitive algorithms, especially for high-order modulation. The OTA test further verifies its feasibility to real environments and indicates its potential for future communications systems.

IEEE 802.11 기반 시스템에서 채널추정에 관한 연구

Abstract Wireless LAN system is evolving toward high-speed data transmission and more accurate channel estimation is necessarily required to improve communication performance. The PLCP preamble field in IEEE 802.11 based wireless MODEM consists of ten short symbols and two long symbols and is used for synchronization and channel estimation. The existing least square (LS) channel estimation is based on only two long training symbols. After estimating channel response separately by using each long training symbol, the final channel estimation is obtained by the average of each estimation. In this paper, a new channel estimation algorithm is presented to improve the performance of the existing LS channel estimation algorithm. From the fact that the short training symbol consists of 12 non-zero subcarriers, it gives us a clue of being able to additionally estimate at least one fourth of channel coefficients. The new LS algorithm performs channel estimation based on both two long training symbols and a short training symbol. The proposed LS algorithm shows a little bit performance improvement over the existing LS estimation and it will be able to be applied to the IEEE 802.11p WAVE system.

Channel Estimation and Combining Orthogonal Pilot Design in MIMO-OFDM System

The current technology of high speed wireless communication exist the following weaknesses, limited bandwidth, bad transmitted channel, complex mobile environment and the quality of service under limited service time. The dispersing pilot pattern and the method of channel estimation using in MIMO-OFDM system couldn’t eliminate the same frequency interference caused by the OFDM frequency among different transmit-receive antenna couples. Aiming at these problems, we proposed a method of MIMO-OFDM channel estimation combining orthogonal pilot design. The data format of pilot is designed. It can retain the orthogonality of different sub-carriers of OFDM which are produced by different transmit-receive antenna couples or transmit-receive antenna couple. In wireless mobile environment, it can better estimate the channel parameters without any prior channel information. This method proposed in the paper has finished the design of the completely orthogonal pilot data symbol among the different subcarriers position of different transmitting-receiving antenna pair. And the pilot data symbols are distributed in the entire time-frequency grid of the channel reasonably, therefore this paper uses a FFT unit whose points are equal to the number of the OFDM subcarriers to realize the least-square channel estimation algorithm. In the process of channel estimation, the channel parameters estimation precision has increased because of the noise getting better inhibition, which reduces the least squares estimate noise sensitivity to the requirements

MIMO Underwater Acoustic Communications in Ports and Shallow Waters at Very High Frequency

Hermes is a Single-Input Single-Output (SISO) underwater acoustic modem that achieves very high-bit rate digital communications in ports and shallow waters. Here, the authors study the capability of Hermes to support Multiple-Input-Multiple-Output (MIMO) technology. A least-square channel estimation algorithm is used to evaluate multiple MIMO channel impulse responses at the receiver end. A deconvolution routine is used to separate the messages coming from different sources. This paper covers the performance of both the channel estimation and the MIMO deconvolution processes using either simulated data or field data. The MIMO equalization performance is measured by comparing three relative root mean-squared errors (RMSE), obtained by calculations between the source signal (a pseudo-noise sequence) and the corresponding received MIMO signal at various stages of the deconvolution process; prior to any interference removal, at the output of the Linear Equalization (LE) process and at the output of an interference cancellation process with complete a priori knowledge of the transmitted signal. Using the simulated data, the RMSE using LE is −20.5 dB (where 0 dB corresponds to 100% of relative error) while the lower bound value is −33.4 dB. Using experimental data, the LE performance is −3.3 dB and the lower bound RMSE value is −27 dB.

A Modified LS Channel Estimation Algorithm for OFDM System in Mountain Wireless Environment

Orthogonal frequency division multiplexing (OFDM) is a transmission technique that is based on many orthogonal carriers that are transmitted simultaneously. OFDM effectively mitigates inter symbol interference (ISI) and has high-efficient frequency utilization. OFDM channel estimation is one of the key technologies in the OFDM system. In this paper, channel estimation techniques for OFDM systems, based on pilot-aided channel estimation algorithm, over mountain wireless environment are investigated. It is well known that least square (LS) and linear minimum mean square error (LMMSE) algorithms are effectual channel estimation methods for OFDM. We propose a novel modified LS channel estimation method, which is based on noise reduction procedure to improve the channel estimation accuracy. The simulation results demonstrate that comparing to LS channel estimation algorithm, LMMSE algorithm and the proposed modified LS algorithm provide better performances.