Effects Of Intersymbol Interference Research Articles

Deep Learning Equalizer Connected with Viterbi-Viterbi Algorithm for PAM D-Band Radio over Fiber Link.

D-band (110-170 GHz) has been regarded as a potential candidate for the future 6G wireless network because of its large available bandwidth. At present, the lack of electrical amplifiers operating in the high frequency band and the strong nonlinear effect, i.e., the D-band, are still important problems. Therefore, effective methods to mitigate the nonlinear issue resulting from the ROF link are indispensable, among of which machine learning is considered the most effective paradigm to model the nonlinear behavior due to its nonlinear active function and structure. In order to reduce the computation amount and burden, a novel deep learning neural network equalizer connected with typical mathematical frequency offset estimation (FOE) and carrier phase recovery (CPR) algorithms is proposed. We implement D-band 45 Gbaud PAM-4 and 20 Gbaud PAM-8 ROF transmission simulations, and the simulation results show that the real value neural network (RVNN) equalizer connected with the Viterbi-Viterbi algorithm exhibits better compensation ability for nonlinear impairment, especially when dealing with serious inter-symbol interference and nonlinear effects. In our experiment, we employ coherent detection to further improve the receiver sensitivity, so a complex baseband signal after down conversion at the receiver is inherently produced. In this scenario, the complex value neural network (CVNN) and RVNN equalizer connected with the Viterbi-Viterbi algorithm have better BER performance with an error rate lower than the HD-FEC threshold of 3.8 × 10-3.

Adaptive Hybrid Iterative Linearization Algorithms for IM/DD Optical Transmission Systems

For optical field recovery and linear dispersion compensation, we propose a performance-enhanced linearization algorithm, termed adaptive hybrid multi-constraint iteration algorithm (MCIA), which does not require any physical modifications to standard configurations of intensity-modulation and direct-detection (IM/DD) transmission systems. To improve the sensitivity to the residual inter-symbol interference (ISI) effect, we introduce, after fiber backward-propagation, a linear feed-forward equalizer (FFE) pair into the proposed algorithm. To improve the sensitivity to fiber dispersion estimation errors, we utilize a two-stage dispersion estimator coupled with the G-S iteration. After 100-Gb/s PAM-4 signal transmissions over 400-km fibers, the simulation results show that the MCIA offers a 1.5-dB optical signal-to-noise ratio (OSNR) gain and a 1-dB optical power budget improvement compared with the decision-directed data-aided iterative algorithm (DD-DIA), for highly dispersive IM/DD transmissions. By performing adaptive dispersion estimation, the MCIA has higher tolerance to estimation errors in fiber length. Moreover, for cases subject to large dispersion, the usage of the embedded FFE pair not only desensitizes the MCIA on the limited bandwidth effect, but also accelerates the convergence performance for reaching lower BERs. We experimentally demonstrate that the proposed algorithm can support 150-Gb/s PAM-4 transmissions over 25-km standard single mode fibers (SSMF), where just a 7-tap FFE-pair is required. For 150 Gb/s transmissions, the tolerance to fiber length estimation error is increased from 0.9 km to 20 km.

MODELING OF A DIGITAL COMMUNICATION SYSTEM WITH INTERFERENCE-RESISTANT CODING OVER DELAYED MULTIPATH CHANNELS FOR A FIXED WIRELESS ACCESS SYSTEM


 
 
 In this study, an analysis of the performance of a digital communication system was conducted to improve the efficiency of the communication channel. The system was de- signed and evaluated in the MatLab/Simulink environment, specifically for the transmission of binary data in a multipath channel with static fading. One of the main advantages of this system is its ability to provide high noise immunity, even in the presence of noise, interference, and signal delays. The performance of the system was investigated in terms of bit error rate (BER) over both an additive white Gaussian noise (AWGN) channel and a multipath Rayleigh fading channel. The study also considered the impact of inter-symbol interference (ISI) and explored different parameters for a static channel, resembling a wireless LAN system based on IEEE 802.11 (as defined by Rec ITU-R M.1225). This study uses a solution to suppress inter-symbol interference using cascading coding (convolutional turbo codes with Reed Solo- mon code), Fast Fourier Transform (FFT) and Inverse Fast Fourier Transform (IFFT), amplifiers at the transmitter side and normalizer at the receiver side, by regulating the amplification ratios of transmitter and receiver sides. Modeling of a digital communication system for a wide-band fixed wireless LAN system (for Indoor office and Outdoor to indoor systems) has been performed. The modeling outcomes show that the applied method provides a good per- formance improvement in channels with ISI with static fading.
 The application of cascading coding (turbo code together with RS code), amplifiers, and FFT on the transmitter side, and IFFT on the receiver side will eliminate the effects of inter-symbol interference on digital signals in a multipath channel with static fading (as defined by Rec. ITU-R M.1225 for internal and external transmission systems) for wireless fixed systems.
 
 

M-Ary Direct Modulation Chirp Spread Spectrum for Spectrally Efficient Communications

Spread spectrum techniques, such as the Chirp Spread Spectrum (CSS) used by LoRa technology, are important for machine-to-machine communication in the context of the Internet of Things. They offer high processing gain, reliable communication over long ranges, robustness to interference and noise in harsh environments, etc. However, these features are compromised by their poor spectral efficiency, resulting in a very low data transmission rate. This paper deals with a spectrally efficient variant of CSS. The system uses M-ary phase keying to modulate the data and exploits CSS’s properties to transmit the modulated symbols as overlapping chirps. The overlapping of chirp signals may affect the system performance due to inter-symbol interference. Therefore, we analyse the relationship between the number of overlaps and the effect of inter-symbol interference (ISI), and we also determine the BER expression as a function of the number of overlaps. Finally, we derive the optimal number of overlapping symbols that corresponds to the minimum error probability.

Analysis of a WDM system with a modified duobinary modulation scheme in an optical network using EDFA.

Advanced modulation format is a promising solution to accomplish improved bandwidth exploitation for quality transmission in optical networks. This paper proposes a modified duobinary modulation in an optical communication network, and the proposed system is compared with the preceding modulation scheme of duobinary modulation without a precoder and duobinary modulation with a precoder. Ideally, two or more signals are transmitted over single-mode fiber using a multiplexing method. Hence, wavelength division multiplexing (WDM) using an erbium-doped fiber amplifier (EDFA) as an active optical network is utilized to improve the quality factor and reduce the effect of intersymbol interference in optical networks. The performance of the proposed system is analyzed for parameters such as quality factor, bit error rate, and extinction ratio using OptiSystem 14 software.

Oversampling-Based Combining Under ISI Channels

We propose in this letter the oversampling based combining scheme under inter-symbol interference (ISI) channels, where the receiver samples the received signal at the rate that is higher than the symbol rate and performs combining over the channel length for each transmitted symbol. We show that by increasing the sampling rate, the achievable rate of the proposed scheme approaches the achievable rate of the ISI-free scheme in multi-path channels. Furthermore, we prove that if the sufficient condition is satisfied, then increasing the sampling rate makes the proposed scheme eliminate the effect of ISI so that the signal to interference-plus-noise ratio (SINR) for the output of the combiner approaches the SNR for AWGN channel (without fading and without ISI). This result leads to the facts that the error probability of the proposed scheme can approach that of AWGN channel and the achievable rate of the proposed scheme can approach the channel capacity of AWGN channel. The proposed scheme is a linear scheme and the achievable rate of the proposed scheme can be close to the channel capacity of AWGN channel with small increase in the computational complexity.

Physical Layer Security for Visible Light Communication in Reflected Indoor Environments With Inter-Symbol Interference

Visible light communication (VLC) is a promising technology for next-generation indoor wireless broadband communication systems. Physical layer security (PLS) is one proposed method to ensure data security for VLC in public areas. However, most PLS studies in the literature neglect the reflections in the VLC channel and do not consider inter-symbol interference (ISI). This paper investigates the ISI effects on the secrecy rate in multiple-input single-output VLC systems where the reflections are not neglected for the cases of perfect and imperfect knowledge of the eavesdropper’s channel state information. We aim to compensate for the ISI effects by designing zero-forcing (ZF) and artificial noise (AN) beamformers. In addition, we formulate optimization problems to maximize the secrecy rate resulting in non-convex and NP-hard problems. Thus, we utilize the particle swarm optimization algorithm for solutions and also convert non-convex optimization problems into easily solvable linear problems. Furthermore, robust ZF and AN beamformers for the worst-case scenario are considered for the cases of ISI and no ISI. The results reveal that ISI severely degrades the secrecy rate; however, well-designed beamformers can reverse the ISI effects.

Rolling Shutter OFDM Scheme for Optical Camera Communication Considering Mobility Environment Based on Deep Learning

This paper presents a rolling shutter orthogonal frequency-division multiplexing (RS-OFDM) optical camera communication higher rate longer range proposed in IEEE 802.15.7a Task Group (TG7a) using an image sensor as a receiver. OFDM is a digital multi-carrier modulation scheme deployed for broadband wireless communication to resolve the inter-symbol interference (ISI) effect caused by the multipath channel. In optical wireless communication systems, OFDM was applied widely for indoor applications: internet of things, e-health, vehicular, and localization systems. The mobility scenario is a big problem for OWC systems, which reduces the system performance due to the optical channel variation in the processing time. In addition to that, signal detection should be considered in the mobility environment to improve the signal-to-noise ratio of OWC systems. In this paper, we proposed the convolution neural network (CNN) for LED detection in the RS-OFDM system, considering the mobility effect. In addition to that, the deep neural network was applied to detect the start of OFDM frame instead of conventional technology (Van De Beek algorithm). By applying our approach, the RS-OFDM system can achieve long communication (18 m distance) with a low error rate in the 2 m/s velocity environment.

Robust Frequency-Domain Timing Offset Estimation for DCO-OFDM Systems

Optical wireless communication (OWC) systems suffer inter-symbol interference (ISI) in time domain due to light emitting diode (LED)’s limited bandwidth at transmitter. As intensity modulation and direct detection (IM/DD) is used, the transmitted signals are unipolar and real-valued rather than bipolar and complex-valued as in radio frequency (RF). Thus, it is challenging to employ the RF-based timing offset estimation for OWC. Also, there is no carrier frequency offset (CFO) like in RF. It is possible to estimate timing offset in frequency domain for two reasons. First, the effect of ISI in time domain is mitigated in frequency domain with correct timing offset estimation, robust against LED’s limited bandwidth. Second, the correlation between frequency-domain signals are high, as signals are bipolar and complex-valued in frequency domain rather than unipolar and real-valued in time domain. Therefore, we propose an effective frequency-domain timing offset estimation approach for direct current biased optical-orthogonal frequency division multiplexing (DCO-OFDM) OWC systems, where a small number of pilots are applied on few DCO-OFDM subcarriers, leading to very low spectral overhead. The property of no CFO is utilized to formulate an error function, by exploring the correlation between received signals and pilots. We propose a squared error function (SEF)-based timing offset estimation approach, conducted by maximizing the ratio of two successive variances of squared errors. Simulation results show that, with a very low training overhead of 0.48%, the proposed SEF-based approach provides a bit error ratio (BER) performance close to ideal case with perfect timing offset estimation, perfect channel state information and zero-forcing (ZF) equalization.

Performance evaluation of MIMO DFT-Spread WR-OFDM system for spectrum efficiency and power efficiency

ABSTRACT It is important to design a spectrum-efficient and power-efficient wireless communication system, which is the main design target in cellular and wireless communication engineering. Basically, to make it, the desired system must have a low peak-to-average power ratio (PAPR), low-level of out-of-band (OOB) power emission and can provide a high throughput. In this paper, we propose a high-throughput cellular communication system, namely Discrete Fourier Transform-Spread Windowing and Restructuring Orthogonal Frequency Division Multiplexing (DFT-Spread WR-OFDM), which has considerably low PAPR and low OOB power emission for upcoming next-generation beyond 5G (B5G) and 6G cellular communication systems. High PAPR is still one of the challenging issues for the MIMO-OFDM system. The proposed system is an effective arrangement of DFT-Spreading and windowing techniques to reduce PAPR and OOB power emission, respectively. Multiuser diversity is obtained using localized subcarrier mapping. We take advantages of spatial multiplexing to enhance the data throughput significantly. Additionally, frequency-domain equalization (FDE)-minimum mean squared error (MMSE) is used to combat the inter-symbol interference (ISI) effect. Simulation results verify that the suggested system considerably lowers PAPR and OOB power emission compared to the conventional systems. Furthermore, the proposed scheme shows better bit error rate (BER) performance over the MIMO Rayleigh fading channel environment. Simulation results also confirmed that the channel capacity of our suggested system is better than the conventional multi-carrier systems.

Frequency Domain Detection and Precoding for Massive MIMO With Single Carrier Modulation

Single carrier modulation (SCM) schemes are attractive for uplink (UL) transmissions due to improved power efficiency at the user equipment (UE) transmitter compared with multi-carrier modulation schemes. In a massive MIMO scenario with SCM, the UL detection must mitigate the effects of inter-symbol interference and multi-user interference. This processing is effectively performed in the frequency domain (FD) using a minimum mean squared error (MMSE) detector when the transmission is framed with a cyclic prefix. This paper analyzes an MMSE-based detector compatible with distributed processing in a time-division duplex (TDD) system. The matrix inverses computed for the UL detection are then reused to perform multi-user precoding for the downlink (DL). We find that this scheme yields tremendous savings in computational complexity compared to commonly used zero-forcing (ZF) precoding without sacrificing any performance. Since MMSE processing introduces a bias to the estimates, we derive the scalar coefficients necessary to cancel the MMSE bias. The impact of channel estimation errors is analyzed for both the UL and DL cases in conjunction with a power-efficient approach to SCM channel estimation. Moreover, extensive simulations are performed to confirm our theoretical findings.

Моделирование каналов связи с многолучевым распространением сигналов процедурами помехоустойчивого кодирования в рамках стандарта LTE

A scheme of orthogonal frequency division multiplexing technologies with a cyclic prefix was used, using the fast Fourier transform algorithm and amplifiers on the transmitter side and a normalizer on the receiver side. By adjusting the gains of the transmitting and receiving sides, the circuit practically makes it possible to reduce situations when inter-symbol interference (ISI) is affected to situations where it does not exist. The proposed model is modeled using Simulink based on MATLAB. The scheme was investigated for the bit error rate (BER) using the additive white Gaussian noise (AWGN) channel and the multipath Rice fading channel operating under the influence of ISI and different parameters for the channel were investigated, where cases of signal delay similar to the EPA standards (Extended Pedestrian A model) were considered. Data transmission in the system includes a Relay channel and AWGN with different values of signal-to-noise ratio (SNR, dB) and different values of Gain, dbGain amplifier. Result: A graph of data transmission performance in a multipath channel with fading with respect to BER and SNR (BER ≈ 0 with values of SNR –21dB) was obtained. The effect of intersymbol interference on the receiver side is also considered by analyzing eye diagrams. The research data can be used in the design of radio engineering devices for data transmission over a wireless network.

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.

Layered Molecular Shift Keying for Molecular Communication via Diffusion

Molecular communication (MC) is a promising communication paradigm for realizing nano-networks, where molecules are employed as an information carrier. In this letter, based on diffusive MC we propose a novel modulation scheme, called layered molecular shift keying (LMoSK), where several types of molecule form different layers to encode information bits, which can not only improve the data rate but also reduce the effect of inter-symbol interference (ISI). For detection of LMoSK, we formulate an ideal maximum likelihood (ML) receiver assuming knowledge of the ISI. Considering the limited capability of the receiver, we further propose a practical ML detection, enjoying both reduced computational complexity and memory of the receiver. The error performance of the LMoSK with practical ML receiver is analyzed and compared with that of molecular shift keying modulation and molecular type permutation shift keying modulation. Simulation results demonstrate that the proposed LMoSK outperforms benchmark schemes.

EVALUATION OF CHANNEL CODING EFFICIENCY IN OFDM TELECOMMUNICATIONS

The paper presents the results a study of methods for increasing the noise immunity of telecommunication channels with OFDM. The structure of the OFDM signal is investigated. The influence of the structure OFDM signals on the noise immunity of their transmission under the influence of the effect of intersymbol interference in a multipath channel is estimated. Recommendations are given on the choice of the OFDM signal form in order to counteract the influence of intersymbol interference by optimizing the duration of the pulse sequence. The behaviour of OFDM signals in the case of intersymbol interference in the AWGN and the Rayleigh channel is investigated. Recommendations for counteracting interference influence on the quality of communication are given. A comparison is made of the efficiency signal-code constructions based on concatenated codes in the case of their application in channels with OFDM. The article presents the results of the development models of effective coding in telecommunications with OFDM based on concatenated codes, taking into account the coding rate and the number of decoding iterations to ensure the specified noise immunity indicators. At the current stage of implementation of modern telecommunication technologies, the use of channel coding plays a key role in increasing the performance of channels that use OFDM. The main contribution of channel coding in combination with time and frequency interleaving is the formation of inter-bit communication in the data stream transmitted on separate carriers in the signal spectrum in such a way that the transmitted information data in the fading channel can be updated in the receiving equipment. In general, in this case, having frequency selectivity creates a certain advantage through frequency diversity. Thus, the presence of information about the state of the channel in the case of channel coding creates the prerequisites for obtaining a certain gain. Optimal in terms of speed and computational complexity, the selection of the scheme and algorithm for decoding the error-correcting code makes it possible to find a compromise in the design of concatenated circuits in channels with OFDM and ultimately obtain a satisfactory gain in performance.

Evaluation and Reduction of Signal Integrity Issues in Multiwalled Carbon Nanotube On-Chip VLSI Interconnects

Due to advancements in device scaling in very-large-scale integration (VLSI) technology, signal integrity (SI) issues play a major role to determining the performance of on-chip interconnects in high-speed digital circuits. The main SI issues are delays, peak voltage noise effects, crosstalk, and timing uncertainties. Here, the SI issues of the coupled multi-walled carbon nanotube (MWCNT) on-chip interconnects are evaluated with and without the effect of shielding technique and compared to the copper interconnects. The MWCNT exhibits an average of 47.9% smaller propagation delays than Cu in dynamic crosstalk conditions. Further, for crosstalk reduction, the active shielding (AS) and passive shielding (PS) techniques are proposed. With the AS and PS techniques, the MWCNT interconnects experience a decreased delay by 46.8% and 30.15% compared to without shielding technique, respectively. Moreover, the AS exhibits smaller crosstalk effects than the PS technique due to its input switching activities on shielded lines. In addition, the quality of the signal (QoS) and Intersymbol interference (ISI) noise effects of coupled MWCNT interconnect with and without shielding is evaluated. Finally, to improve the QoS and reduce the ISI effects, the decision feedback equalizer with the least mean square adaptive algorithm is implemented at the receiver end.

Error correction in data storage systems using polar codes

This paper investigates error correction in two-dimensional (2-D) intersymbol interference (ISI) channels using polar codes. 2-D channels offer high data storage capacity compared to traditional one-dimensional (1-D) channels but suffer from greater ISI effects. Error correction codes can be used to mitigate the effects of ISI in 2-D data storage systems and improve their performance and reliability. Polar codes achieve the symmetric capacity for the class of binary-input discrete memoryless channels (B-DMCs). A post-processing technique is proposed to improve the performance of polar codes in the 2-D ISI channel. The simplified successive cancellation (SSC) polar decoder is useful for data storage systems owing to its good waterfall region performance, low error floors and good throughput rates and is therefore adopted for the study. Simulation results indicate that the proposed technique has an error correction performance comparable to some existing decoders and has better performance than other decoding techniques.

Least minimum symbol error rate based post-distortion for adaptive mobile VLC transmission with receiver selection

In the context of beyond-5G indoor communication systems, visible light communication (VLC) has emerged as a viable supplement for existing RF-based systems and as an enabler for high data-rate communications. However, the existing indoor VLC systems are limited by detrimental outages caused by fluctuations in the VLC channel-gain due to user-mobility. Furthermore, the nonlinear characteristics of the light-emitting diode (LED) degrade the performance of VLC systems in the high-power regime by warping the input constellation. Additional performance-limits are introduced by inter-symbol interference (ISI) due to finite modulation-bandwidth of LEDs, and reflections from walls. In this paper, a random Fourier feature (RFF) based post-distorter is considered for mitigating the LED nonlinearity, and relevant expressions for the signal to noise ratio (SNR) are derived for a direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) system. Based on the derived expressions for SNR, the effects of user-mobility and ISI are mitigated by a DCO-OFDM based adaptive VLC transmission technique, which varies the transmission-rate/modulation-order under a specified error-rate constraint. Simulations are presented over channels obtained by ray-tracing, which indicates that the proposed algorithm achieves superior data-rates with a significantly lower error-rate.

Optical wireless communication performance enhancement using Hamming coding and an efficient adaptive equalizer with a deep-learning-based quality assessment.

Optical wireless communication (OWC) technology is one of several alternative technologies for addressing the radio frequency limitations for applications in both indoor and outdoor architectures. Indoor optical wireless systems suffer from noise and intersymbol interference (ISI). These degradations are produced by the wireless channel multipath effect, which causes data rate limitation and hence overall system performance degradation. On the other hand, outdoor OWC suffers from several physical impairments that affect transmission quality. Channel coding can play a vital role in the performance enhancement of OWC systems to ensure that data transmission is robust against channel impairments. In this paper, an efficient framework for OWC in developing African countries is introduced. It is suitable for OWC in both indoor and outdoor environments. The outdoor scenario will be suitable to wild areas in Africa. A detailed study of the system stages is presented to guarantee the suitable modulation, coding, equalization, and quality assessment scenarios for the OWC process, especially for tasks such as image and video communication. Hamming and low-density parity check coding techniques are utilized with an asymmetrically clipped DC-offset optical orthogonal frequency-division multiplexing (ADO-OFDM) scenario. The performance versus the complexity of both utilized techniques for channel coding is studied, and both coding techniques are compared at different coding rates. Another task studied in this paper is how to perform efficient adaptive channel estimation and hence equalization on the OWC systems to combat the effect of ISI. The proposed schemes for this task are based on the adaptive recursive least-squares (RLS) and the adaptive least mean squares (LMS) algorithms with activity detection guidance and tap decoupling techniques at the receiver side. These adaptive channel estimators are compared with the adaptive estimators based on the standard LMS and RLS algorithms. Moreover, this paper presents a new scenario for quality assessment of optical communication systems based on the regular transmission of images over the system and quality evaluation of these images at the receiver based on a trained convolutional neural network. The proposed OWC framework is very useful for developing countries in Africa due to its simplicity of implementation with high performance.

BER Analysis of Neural Equalizer in OFDM systems

Digital communication gives larger data capacity and best communication speed. The signal transmitted through the wireless channels in digital communication affected by nonlinearities like noise. Inter Symbol Interference (ISI) dominantly causes huge data loss. It is caused due to multipath propagation, band-limited channels noise. Equalization, a process of inducing inverse channel response to compensate the effects of ISI is used to combat these effects. Orthogonal Frequency Division Multiplexing (OFDM) system supports high data rates and offers resistance towards the channel effect. Adding equalizer to OFDM systems make it more robust.In real time situations the response of channel is not known in prior. So, adaptive equalizers are implemented to compensate channel effects with the help of pilot symbols which are used to estimate the channel response and equalize the signal accordingly. Minimum Mean Square Error (MMSE), Least Square (LS) are some of the existing algorithms used to implement the equalizers. These conventional algorithms require some statistical properties of channel which is not possible in real time scenarios. Also, Linear Transverse equalizer failed to provide satisfactory results in the case of Non Minimum Phase channel. Neural Networks is capable to perform this task and can be used as an alternative to these algorithms.Back Propagation Neural Networks (BPNN) and Deep Neural Networks (DNN) can achieve better results when compared to conventional algorithms. Here, Deep Neural Networks with Adam optimization is proposed to enhance the performance of equalization. DNN can be used in both linear and non-linear channels. Also, Adam optimization used with Back Propagation uses variable and adaptive learning rate which reduces slow convergence and increases the efficiency of neural network unlike stochastic gradient descent which uses fixed learning rate.In this work the performance of proposed equalizer in OFDM systems is analyzed over flat and frequency selective fading of Rayleigh channels. The performance is measured in terms of Bit Error rate over SNR range -30dB to 25 dB. The results are compared with that of MMSE and it is observed that over the mentioned range of SNR the proposed equalizer achieved acceptable results and has low Bit error rate than that of MMSE in both flat and frequency selective fading channels.