Finite Impulse Response Channel Research Articles

Adaptive Channel Equalization for Digital Communication with Tunicate Swarm Algorithm

In wireless communication systems, the information is transferred as digital symbols that get affected by noise interference while transmitting through the wireless channel. In today’s world, the increased demand for rapid data transmission rates leads to more inter-symbol interference in the received signal. To diminish the effects of inter-symbol interference, adaptive channel equalization is utilized in digital communication. In this paper, the inter-symbol interference effect in the finite impulse response channel is reduced in terms of an adaptive equalizer method. The weights/coefficients of the equalizer are optimized through a tunicate swarm algorithm. Channel equalization involves optimizing the channel coefficients to mitigate the impact of inter-symbol interference. This equalization process can be viewed as an iterative optimization task, aimed at lessening the mean square error among the transmitted signal and the equalizer’s output. The implementation of the proposed method is executed using MATLAB software. We assess its effectiveness through a comparative analysis, considering metrics such as mean square error, learning rate, bit error rate, convergence rate, and computational time. Furthermore, we conduct a comparative evaluation with other optimization approaches, including the Bat Algorithm, Slime Mould Algorithm, and Harris Hawks Optimization Algorithm. This comparison demonstrates the superiority of the proposed algorithm over traditional optimization techniques.

A Novel Kernel Algorithm for Finite Impulse Response Channel Identification


 
 
 
 Over the last few years, kernel adaptive filters have gained in importance as the kernel trick started to be used in classic linear adaptive filters in order to address various regression and time-series prediction issues in nonlinear environments.In this paper, we study a recursive method for identifying finite impulse response (FIR) nonlinear systems based on binary-value observation systems. We also apply the kernel trick to the recursive projection (RP) algorithm, yielding a novel recursive algorithm based on a positive definite kernel. For purposes, our approach is compared with the recursive projection (RP) algorithm in the process of identifying the parameters of two channels, with the first of them being a frequency-selective fading channel, called a broadband radio access network (BRAN B) channel, and the other being a a theoretical frequency-selective channel, known as the Macchi channel. Monte Carlo simulation results are presented to show the performance of the proposed algorithm.
 
 
 

A New OFDM System for IIR Channels

In this paper, we propose a new orthogonal frequency division multiplexing (OFDM) system for an infinite impulse response (IIR) channel with the form of B(z)/A(z) for two polynomials A(z) and B(z). Different from the conventional OFDM transmission over a finite impulse response (FIR) channel, a guard interval of an OFDM symbol is added such that the corresponding part at receiver is the cyclic prefix (CP) of the received OFDM symbol. The guard interval and CP lengths are the same and not smaller than the orders of polynomials A(z) and B(z). The OFDM symbol without the guard interval is the same as the conventional OFDM symbol without the CP. At the receiver, the IIR channel is then converted to N intersymbol interference (ISI) free subchannels, where N is the number of subcarriers of an OFDM symbol.

Complexity curtailed MLSE equalizer based on a compact look-up-table for C-band DSB IM/DD transmission.

Chromatic dispersion appears to be a major performance limiting problem in optical intensity modulation direct detection (IM/DD) transmission systems, especially for a double-sideband (DSB) signal. We propose a complexity-reduced look-up-table based maximum likelihood sequence estimation (LUT-MLSE) for DSB C-band IM/DD transmission based on pre-decision-assisted trellis compression and a path-decision-assisted Viterbi algorithm. To further compress the size of the LUT and reduce the length of the training sequence, we proposed a finite impulse response (FIR) and LUT hybrid channel model for the LUT-MLSE. For PAM-6 and PAM-4, the proposed methods can compress the size of the LUT into 1/6 and 1/4, and reduce the number of multipliers by 98.1% and 86.6% with slight performance degradation. We successfully demonstrate a 20-km 100-Gb/s PAM-6 and a 30-km 80-Gb/s PAM-4 C-band transmission over dispersion-uncompensated links.

Adaptive Channel Equalization Using Seagull Optimization with Various Initialization Strategies

In a digital communication channel, the transmitted signal may be dispersive causing the information to not be transmitted as same. Due to the distortion, the communication channel is affected known as Inter-Symbol Interference (ISI). To reducing the ISI effect, adaptive channel equalization plays an important role in digital communication. In the proposed method, the Finite Impulse Response (FIR) channel ISI effect is reduced by the proposed optimization algorithm. The FIR channel weight or coefficients are optimized by the proposed Seagull Optimization Algorithm (SOA) with different initialization strategies. Normally, SOA has random initialization of population but to improve the process of adaptive channel equalization, Random Number Generation (RNG), Opposition based learning (OBL) and Quasi-Opposition based learning (QBL) methods are utilized for initialization. The objective function of the equalization process is minimization error values where the error value is estimated based on the desired signal and channel output signal. The experiment is carried out on the MATLAB platform. The proposed method's effectiveness is shown to compare the various initialization methods of RNG, OBL and QBL with SOA. Based on different SNRs, the error value is computed and shows the convergence results.

FPGA Implementation of Proficient 16-Tap FIR Filter Design Using Decision Tree Algorithm

Lately, channel is one of the key components in signal handling applications. Among different channels, Finite Impulse Response (FIR) channel is broadly utilized in Digital Signal Processing (DSP) applications for shifting/denoising. For enormous scope coordination (VLSI) execution of fixed-coefficient FIR channels, huge asset used customary multipliers that can be acknowledged by a solitary steady multiplication (SCM) and numerous consistent augmentations (MCM) square utilizing movement and include/take away tasks. For a proficient execution, a variable size apportioning approach is proposed in direct structure channel structure that devours less zone and 11% of decrease in basic way delay, 40% decrease of all out force utilization, 15% decrease of zone delay product(ADP), 52% decrease of vitality delay product(EDP), and 42% decrease of intensity territory product(PAP), on a normal, over the cutting edge techniques. In this paper, a state choice tree calculation is proposed to decrease unpredictability in channel tap cells of variable size apportioning approach. The proposed plot creates a choice tree to perform move and expansion/deduction and aggregation dependent on the consolidated SCM/MCM approach. This plan diminishes the quantity of postpone registers required for tab cells. The proposed snake design will be actualized in Xilinx Zed, Spartan and Virtex devices and Area, power and speed investigation will be performed.

FPGA Implementation of Proficient 16-Tap FIR Filter Design Using Decision Tree Algorithm

Lately, channel is one of the key components in signal handling applications. Among different channels, Finite Impulse Response (FIR) channel is broadly utilized in Digital Signal Processing (DSP) applications for shifting/denoising. For enormous scope coordination (VLSI) execution of fixed-coefficient FIR channels, huge asset used customary multipliers that can be acknowledged by a solitary steady multiplication (SCM) and numerous consistent augmentations (MCM) square utilizing movement and include/take away tasks. For a proficient execution, a variable size apportioning approach is proposed in direct structure channel structure that devours less zone and 11% of decrease in basic way delay, 40% decrease of all out force utilization, 15% decrease of zone delay product(ADP), 52% decrease of vitality delay product(EDP), and 42% decrease of intensity territory product(PAP), on a normal, over the cutting edge techniques. In this paper, a state choice tree calculation is proposed to decrease unpredictability in channel tap cells of variable size apportioning approach. The proposed plot creates a choice tree to perform move and expansion/deduction and aggregation dependent on the consolidated SCM/MCM approach. This plan diminishes the quantity of postpone registers required for tab cells. The proposed snake design will be actualized in Xilinx Zed, Spartan and Virtex devices and Area, power and speed investigation will be performed

Video-Capable Ultrasonic Wireless Communications Through Biological Tissues

The use of wireless implanted medical devices (IMDs) is growing because they facilitate monitoring of patients at home and during normal activities, reduce the discomfort of patients and reduce the likelihood of infection associated with trailing wires. Currently, radiofrequency (RF) electromagnetic waves are the most commonly used method for communicating wirelessly with IMDs. However, due to the restrictions on the available bandwidth and the employable power, data rates of RF-based IMDs are limited to 267 kbps. Considering standard definition video streaming requires data rates of 1.2 mbps and high definition requires 3 mbps, it is not possible to use the RF electromagnetic communications for high data rate communication applications such as video streaming. In this work, an alternative method that utilizes ultrasonic waves to relay information at high data rates is introduced. An advanced quadrature amplitude modulation (QAM) modem with phase-compensating, sparse decision feedback equalizer (DFE) is tailored to realize the full potential of the ultrasonic channel through biological tissues. The proposed system is tested in a variety of scenarios, including both simulations with finite impulse response (FIR) channel models, and real physical transmission experiments with ex vivo beef liver and pork chop samples as well as in situ rabbit abdomen. Consequently, the simulations demonstrated that video-capable data rates can be achieved with milimeter-sized transducers. Real physical experiments confirmed data rates of 6.7, 4.4, 4 and 3.2 mbps through water, ex vivo beef liver, ex vivo pork chop and in situ rabbit abdomen, respectively.

A Novel Technique for Achieving the Approximated ISI at the Receiver for a 16QAM Signal Sent via a FIR Channel Based Only on the Received Information and Statistical Techniques.

A single-input-multiple-output (SIMO) channel is obtained from the use of an array of antennas in the receiver where the same information is transmitted through different sub-channels, and all received sequences are distinctly distorted versions of the same message. The inter-symbol-interference (ISI) level from each sub-channel is presently unknown to the receiver. Thus, even when one or more sub-channels cause heavy ISI, all the information from all the sub-channels was still considered in the receiver. Obviously, if we know the approximated ISI of each sub-channel, we will use in the receiver only those sub-channels with the lowest ISI level to get improved system performance. In this paper, we present a systematic way for obtaining the approximated ISI from each sub-channel modelled as a finite-impulse-response (FIR) channel with real-valued coefficients for a 16QAM (16 quadrature amplitude modulation) source signal transmission. The approximated ISI is based on the maximum entropy density approximation technique, on the Edgeworth expansion up to order six, on the Laplace integral method and on the generalized Gaussian distribution (GGD). Although the approximated ISI was derived for the noiseless case, it was successfully tested for signal to noise ratio (SNR) down to 20 dB.

Experimental setup of stretchable arid dry pad sensors for the signal acquisition fir filter design using Vedic approach

At present in Medical Image processing a hard point to settle any issue with the assistance of Computer collaborator using Arid-dry pad sensor plays a prominent role. Specialist is to investigate the medical diagnosis with the assistance of imaging system such as The CT scan, MRI scan, EEG, Ultrasound technique or any kind of medical images analyzing the system of the patient with the help of images. Design of low power and low delay digital finite-impulse response (FIR) which plays a vital role in medical image applications along with Arid-dry pad sensors. These days, there are numerous versatile applications requiring low power and high throughput than any time in recent memory. In this research the FIR channel framework configuration has turned into a huge execution objective. The Finite Impulse Response (FIR) Filter is the vital segment for planning a medical image processing. The adders and multipliers play an important role in FIR filter while considering these, not only the fast response but also the number of component, area and path delay. The proposed FIR filter is designed by using adder and Wave pipelined Vedic multiplier from the analysis of various adders and multipliers. The Wave pipelined Vedic multiplier performs multiplication process in a hierarchical manner. The work has demonstrated the effectiveness of Urdhva Triyagbhyam– Vedic technique for multiplication which strikes a distinction in the real procedure of increase itself. It empowers parallel age of moderate items, wipes out undesirable increase ventures with zeros and scaled to higher bit levels. Thus, the proposed method can minimize the setup time violation and path delay of the FIR filter with pad sensors. The proposed FIR Filter is simulated, synthesized, calculating power consumption using ISE simulator, Xilinx and Altera Quartus II.

Enabling Ultrasound In-Body Communication: FIR Channel Models and QAM Experiments.

Ultrasound waves pose a promising alternative to the commonly used electromagnetic waves for intra-body communication. This due to the lower ultrasound wave attenuation, the reduced health risks, and the reduced external interference. Current state-of-the-art ultrasound designs, however, are limited in their practical in-body deployment and reliability. This stems from their use of bulky, focused transducers, the use of simple modulation schemes or the absence of a realistic test environment and corresponding realistic channel models. Therefore, this paper proposes a new, ultrasound, static emulation test bed consisting of small, omnidirectional transducers, and custom gelatin phantoms with additional scattering materials. Using this test bed, we investigate different in-body communication scenarios. Multiple communication channels were extracted and mapped onto finite impulse response (FIR) channel models, which are verified and open sourced for future research. Furthermore, a basic quadrature-amplitude modulation (QAM) modem was built to assess the communication performance under various modulation schemes. A link was established using 4-QAM and 200kbit/s resulting in a BER <1e-4 at received Eb/No of 13dB. Identical results were obtained by computer simulations on the FIR channels, which makes the extracted FIR channels suitable for the design of future ultrasound in-body communication schemes.

Design of Supervised and Blind Channel Equalizer Based on Moth-Flame Optimization

With the increase in demand of high-speed data, the communication channels are suffering from inter-symbol interference, nonlinearity and noise. In this paper, digital channel equalizers are developed for finite impulse response (FIR) and infinite impulse response (IIR) channels. Supervised learning based on minimum mean square error is opted for FIR channels affected by noise and nonlinearity. For IIR channel, blind equalization based on constant modulus technique is employed. The weights of both type of equalizers are determined by a recently developed nature-inspired algorithm moth-flame optimization (MFO). The performance is compared with the same structure of equalizer trained with standard algorithms like: artificial immune system, adaptive particle swarm optimization, binary genetic algorithm and least mean square algorithm. Simulation studies are demonstrated for equalizers designed to compensate the response of two FIR channels, and both are affected by two nonlinearities with noise and three IIR channels. Superior performance by the proposed MFO equalizer is reported based on frequency response analysis, mean square error during training and BER plots during testing.

PN sequence blind estimation in multiuser DS‐CDMA systems with multipath channels based on successive subspace scheme

SummaryIn this paper, we proposed a new method based on expanding subspace algorithm and finite alphabet characteristics, for blind estimation of the users' spreading sequences in the multiuser direct sequence code division multiple access system in the presence of the multipath channels. In the proposed scheme, we show that the estimation of the users' overall channels in the direct sequence code division multiple access system is equivalent to the impulse response estimation of the multi‐input multi‐output finite impulse response channels. Our proposed approach is based on the successive estimation of the columns of the equivalent multi‐input multi‐output finite impulse response channels from the lowest degree columns to the highest degree ones. Accordingly, each user's overall channel that is the convolution of the original multipath channel and the spreading sequence is estimated. Then we extract PN sequences from the overall channel using finite alphabet characteristics of the spreading sequence chips for each user. According to simulation results, our proposed scheme outperforms the conventional methods in that it does not require symbol synchronization and does not have channel constraints (for example, AWGN and single user system) in the multipath channels.

Precoding-Based Blind Separation of MIMO FIR Mixtures

This paper focuses on the problem of blind separation of sources mixed by multi-input multi-output finite impulse response channels, which is also called convolutive blind source separation (BSS) in short. This problem has been intensively studied in the context that the sources possess certain favourable properties, such as independence and sparsity. However, these properties may not exist in some practical applications. In this paper, we propose a precoding-based convolutive BSS method, which can deal with mutually correlated sources without requiring the sources to be sparse. It is also applicable to mutually independent sources. In the proposed method, the sources are preprocessed in transmitters prior to transmission by order-one precoders. At the receiving side, the second-order statistics of the sources and the $Z$ -domain features of the precoders are exploited to estimate the coded signals, from which the sources are recovered. Simulation results demonstrate the effectiveness of the new convolutive BSS method.

A second-order blind equalization method robust to ill-conditioned SIMO FIR channels

This paper deals with blind equalization of single-input–multiple-output (SIMO) finite-impulse-response (FIR) channels driven by i.i.d. signal, by exploiting the second-order statistics (SOS) of the channel outputs. Usually, SOS-based blind equalization is carried out via two stages. In Stage 1, the SIMO FIR channel is estimated using a blind identification method, such as the recently developed truncated transfer matrix (TTM) method. In Stage 2, an equalizer is derived from the estimate of the channel to recover the source signal. However, this type of two-stage approach does not give satisfactory blind equalization result if the channel is ill-conditioned, which is often encountered in practical applications. In this paper, we first show that the TTM method does not work in some situations. Then, we propose a novel SOS-based blind equalization method which can directly estimate the equalizer without knowing the channel impulse responses. The proposed method can obtain the desired equalizer even in the case that the channel is ill-conditioned. The performance of our method is illustrated by numerical simulations and compared with four benchmark methods.

Adaptive matching pursuit using coordinate descent and double residual minimization

We present a greedy recursive algorithm for computing sparse solutions to systems of linear equations. Derived from adaptive matching pursuit, the algorithm employs a greedy column selection strategy which, combined with coefficient update via coordinate descent, ensures a low complexity. The sparsity level is estimated online using the predictive least squares (PLS) criterion. The key to performance is the minimization of two residuals, corresponding to two solutions with different sparsity levels, one for finding the values of the nonzero coefficients, the other for maintaining a large enough pool of candidates for the PLS criterion. We test the algorithm for a sparse time-varying finite impulse response channel; the performance is comparable with or better than that of the competing methods, while the complexity is lower.

Subspace-based blind channel estimation in nearly saturated down link multicarrier code division multiple access systems

A new subspace-based blind method for channel estimation in nearly saturated downlink multicarrier code division multiple access systems is proposed. In this method, the authors exploit the subspace structure of the received signal to estimate the channel directly in the frequency domain irrespective of the length of the finite impulse response (FIR) channel, thus allowing operation in nearly saturated systems (number of users can be one less than process gain). The method is shown to outperform some earlier blind channel estimation methods, whereas at the same time avoiding the limitations in the number of users that these methods suffer from.

Semiblind Sparse Channel Estimation for MIMO-OFDM Systems

In this paper, a semiblind algorithm is presented for the estimation of sparse multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) channels. An analysis of the second-order statistics of the signal that was received through a sparse MIMO channel is first conducted, showing that the correlation matrices of the received signal can be expressed in terms of the most significant taps (MSTs) of the sparse channel. This relationship is used to derive a blind constraint for the effective channel vector that corresponds to the MST position. The blind constraint is then combined with the training-based least square criterion to develop a semiblind approach for the estimation of MSTs of the sparse channel. A signal perturbation analysis of the proposed approach is conducted, showing that the new semiblind solution is not subject to the signal perturbation error when the sparse channel is a decimated version of a full finite impulse response channel. Furthermore, the proposed sparse semiblind algorithm has been extended for the estimation of channels in the upsampling domain for MIMO-OFDM systems with pulse shaping. A number of computer-simulation-based experiments for various sparse channels are carried out to confirm the effectiveness of the proposed semiblind approach.

COMBINED ADJUSTED STEP SIZE LMS ALGORITHM AND ACTIVE TAP DETECTION TECHNIQUE FOR ADAPTIVE NOISE CANCELLATION

In this paper ,a new idea to combine Adjusted Step Size Least Mean Square (ASSLMS) algorithm with standard LMS active tap detection technique is presented .Then the combined method is used for estimating unknown time-invariant (stationary) and time varying (non- stationary) Finite Impulse Response (FIR) channel for adaptive noise cancellation (ANC) application. The focus of this paper is to improve the convergence rate and low level of the error in the steady state for the popular LMS adaptive filter. The simulation results have shown improvement on the convergence rate using the combined technique over both the ASSLMS algorithm and standard LMS active tap detection technique if they are used alone.

Joint Downlink Beamforming and Time-Reversed Matched Filtering for Multiuser UWB Signals

This paper proposes a simple delay-line (DL) downlink beamformer for pulsed ultra-wideband (UWB) systems to compensate for propagation delay, which is detrimental to UWB signals. Moreover, we propose a prefiltering-based transmission scheme at the fixed access point (i.e., base station) by shifting the signal processing needs from the receiver at the mobile unit to the transmitter where power and computational resources are plentiful. The DL transmitter array can steer signals to the direction of the desired mobile user such that the desired signals stemming from each antenna are coherently combined and the multiuser interference (MUI) is averaged out. Furthermore, the prefiltering scheme is composed of a set of time-reversed matched filters (TR MFs) subject to multiple-input single-output (MISO) finite impulse response (FIR) channels. A simple correlation receiver is proposed at the mobile unit to extract the information of the time-hopping (TH) UWB signal. The performances under different scenarios are extensively evaluated.