This paper proposes an analytical model for evaluating the performance of dense wavelength Division Multiplexing (DWDM) for all optical Orthogonal Frequency Division Multiplexing (AO-OFDM) optical wireless channel. The investigated performance for proposed system is evaluated for the parameters bit error rate (BER) and Q factor. The constellation diagrams, and bit error rate (BER) of the received signals are specified. The effect of atmospheric attenuation of the outdoor wireless optical communication system was induced (channel impairments) such as medium rain, light rain, and dust to find their effects on system performance carrier wavelength. The results show the BER and constellation diagram under different weather conditions for different transmission distance using Quadrature Amplitude Modulation (QAM) AO-OFDM-optical wireless channel (OWC).

This paper presents an empirical mode decomposition (EMD) based adaptive filter (AF) for channel estimation in OFDM system. In this method, length of channel impulse response (CIR) is first approximated using Akaike information criterion (AIC). Then, CIR is estimated using adaptive filter with EMD decomposed IMF of the received OFDM symbol. The correlation and kurtosis measures are used to select the useful IMF component from among available IMFs. Conventional AF uses random initial weight vector. The novelty of the proposed method is that it uses decimated version of one of the decomposed IMFs of received OFDM symbol as initial weight vector. This makes the proposed EMD based AF method converge to minimum mean square error (MMSE) in less number of iterations resulting in almost 50% saving of computations. The simulation studies in terms of bit error rate (BER) and mean square error (MSE) calculations established the efficacy of proposed method; and comparative studies under different modulation schemes and fading conditions revealed improved performance.

Due to the increase of users the efficient usage of spectrum plays an important role in digital terrestrial television networks. In digital video broadcasting, local and global content are transmitted by single Frequency network and multiFrequency network respectively. MultiFrequency network support transmission of global content and it consumes large spectrum. Similarly local content are well supported by single Frequency network. In order to provide better spectral efficiency both local and global contents are transmitted in single constellation using hierarchical modulation. Hierarchical modulated OFDM system provides good spectral efficiency and robustness to the fading environment. In this paper a hierarchical modulated OFDM system for local service insertion is analyzed and its performance under various channels is been discussed. Convolutional encoder is used in this paper.

Channel estimation is a crucial task for Orthogonal Frequency Division Multiplexing (OFDM) modulation-based systems since this estimation is used for compensating impacts of a wireless channel. Recently, sparse representation (SR) is proposed for this task as wireless channels are considered as a sparse signal. However, SR considers sparse as the main feature and omit other features of the channel while estimating the channel. In this paper, we propose a general framework for utilizing other features of the channel in sparse channel estimation for OFDM systems, while these features are omitted in conventional sparse methods. In this regard, by utilizing maximum a posterior (MAP) estimation and defining new parameters, these features are conveyed into sparse channel estimation process to improve channel estimation. The simulation results indicate that our proposed framework not only improves the estimated parameter, but also reduces the number of resources such as the number of estimation pilots or transmitted power.

In this paper, a combination of channel, receiver Frequency-dependent IQ imbalance, and carrier Frequency offset estimation under short cyclic prefix length is considered in Orthogonal Frequency Division Multiplexing system. An adaptive algorithm based on the set-membership filtering algorithm is used to compensate for these impairments. In short CP length, per-tone equalization structure is used to avoid inter-symbol interference. Due to CFO impairment and IQ imbalance in the receiver, we will expand the PTEQ structure to a two-branch structure. This structure has high computational complexity, so using the set-membership filtering idea with variable step size while reducing the average computation of the system can also increase the convergence speed of the estimates. On the other hand, applying wavelet transform on each branch of this structure before applying adaptive filters will increase the estimation speed. The proposed algorithm will be named SMF-WP-NLMS-PTEQ. The results of the simulations show better performance than the usual adaptive algorithms. Besides, estimation and compensation of channel effects, receiver IQ imbalance and carrier Frequency offset under short CP can be easily accomplished by this algorithm.

Secret key extraction is a crucial issue in physical layer security and a less complex and, at the same time, a more robust scheme for the next generation of 5G and beyond. Unlike previous works on this topic, in which Orthogonal Frequency Division Multiplexing (OFDM) sub-channels were considered to be independent, the effect of correlation between sub-channels on the secret key rate is addressed in this paper. As an assumption, a realistic model for dependency among sub-channels is considered. Benchmarked by simulation, the result shows that the key exchange rate may decline by up to 72% due to the correlation of sub-channels. A new approach for efficient key extraction is used in this study. To do this, a Singular Value Decomposition based (SVD-based) pre-coding is utilized to alleviate the sub-channels correlation and the channel noise. The low computational complexity of our proposed approach makes it a promising candidate for developing secure and high-speed networks. Results obtained through simulation indicate that applying pre-coding on the measured correlated data resulted in a minimum gain of 9 dB. In addition, the result also depicts the advantage of SVD versus other pre-coding techniques, namely PCA, DCT, and WT.

In the present paper, a 16-channel implantable wireless neural recording system is presented. The proposed system employs Frequency-Division Multiplexing (FDM) to transfer multiple neural channels to an external setup wirelessly. The main advantage of the proposed system is that, while increasing the number of channels, it efficiently utilizes the limited bandwidth allocated for wireless data transmission such as the 402-405 MHz, 174-216 MHz, or 88-108 MHz bands allocated for medical implant communication services. In this system, neural activities from multiple channels are detected using two-dimensional or three-dimensional microelectrodes. After preconditioning, the multiple parallel channels are multiplexed in the Frequency domain within the FDM module. As a result of FDM, preconditioned neural signals are placed in the Frequency domain with 100kHz spacing, occupying a 1600kHz bandwidth starting from 10MHz. Finally, the resulting FDM band is shifted in the Frequency domain by the Frequency modulation (FM) block with a carrier Frequency of 100 MHz. A 16-channel prototype system is designed and simulated using 0.18 µm CMOS technology, with a chip area of 0.55 × 0.58 mm²and a power consumption of 3.35 mW at a supply voltage of 1.8V.