Frequency Domain Independent Component Analysis Applied To Wireless Communications Over Frequency-selective Channels

In wireless communications, frequency-selective fading is a major source of impairment for wireless communications. In this research, a novel Frequency-Domain Independent Component Analysis (ICA-F) approach is proposed to blindly separate and deconvolve signals traveling through frequency-selective, slow fading channels. Compared with existing time-domain approaches, the ICA-F is computationally efficient and possesses fast convergence properties. Simulation results confirm the effectiveness of the proposed ICA-F. Orthogonal Frequency Division Multiplexing (OFDM) systems are widely used in wireless communications nowadays. However, OFDM systems are very sensitive to Carrier Frequency Offset (CFO). Thus, an accurate CFO compensation technique is required in order to achieve acceptable performance. In this dissertation, two novel blind approaches are proposed to estimate and compensate for CFO within the range of half subcarrier spacing: a Maximum Likelihood CFO Correction approach (ML-CFOC), and a high-performance, low-computation Blind CFO Estimator (BCFOE). The Bit Error Rate (BER) improvement of the ML-CFOC is achieved at the expense of a modest increase in the computational requirements without sacrificing the system bandwidth or increasing the hardware complexity. The BCFOE outperforms the existing blind CFO estimator [25, 128], referred to as the YG-CFO estimator, in terms of BER and Mean Square Error (MSE), without increasing the computational complexity, sacrificing the system bandwidth, or increasing the hardware complexity. While both proposed techniques outperform the YG-CFO estimator, the BCFOE is better than the ML-CFOC technique. Extensive simulation results illustrate the performance of the ML-CFOC and BCFOE approaches

Advanced Coding And Modulation For Ultra-wideband And Impulsive Noises

The ever-growing demand for higher quality and faster multimedia content delivery over short distances in home environments drives the quest for higher data rates in wireless personal area networks (WPANs). One of the candidate IEEE 802.15.3a WPAN proposals support data rates up to 480 Mbps by using punctured convolutional codes with quadrature phase shift keying (QPSK) modulation for a multi-band orthogonal frequency-division multiplexing (MB-OFDM) system over ultra wideband (UWB) channels. In the first part of this dissertation, we combine more powerful near-Shannon-limit turbo codes with bandwidth efficient trellis coded modulation, i.e., turbo trellis coded modulation (TTCM), to further improve the data rates up to 1.2 Gbps. A modified iterative decoder for this TTCM coded MB-OFDM system is proposed and its bit error rate performance under various impulsive noises over both Gaussian and UWB channel is extensively investigated, especially in mismatched scenarios. A robust decoder which is immune to noise mismatch is provided based on comparison of impulsive noises in time domain and frequency domain. The accurate estimation of the dynamic noise model could be very difficult or impossible at the receiver, thus a significant performance degradation may occur due to noise mismatch. In the second part of this dissertation, we prove that the minimax decoder in \cite, which instead of minimizing the average bit error probability aims at minimizing the worst bit error probability, is optimal and robust to certain noise model with unknown prior probabilities in two and higher dimensions. Besides turbo codes, another kind of error correcting codes which approach the Shannon capacity is low-density parity-check (LDPC) codes. In the last part of this dissertation, we extend the density evolution method for sum-product decoding using mismatched noises. We will prove that as long as the true noise type and the estimated noise type used in the decoder are both binary-input memoryless output symmetric channels, the output from mismatched log-likelihood ratio (LLR) computation is also symmetric. We will show the Shannon capacity can be evaluated for mismatched LLR computation and it can be reduced if the mismatched LLR computation is not an one-to-one mapping function. We will derive the Shannon capacity, threshold and stable condition of LDPC codes for mismatched BIAWGN and BIL noise types. The results show that the noise variance estimation errors will not affect the Shannon capacity and stable condition, but the errors do reduce the threshold. The mismatch in noise type will only reduce Shannon capacity when LLR computation is based on BIL

Artificial Intelligence Aided Receiver Design for Wireless Communication Systems

Physical layer (PHY) design in the wireless communication field realizes gratifying achievements in the past few decades, especially in the emerging cellular communication systems starting from the first generation to the fifth generation (5G). With the gradual increase in technical requirements of large data processing and end-to-end system optimization, introducing artificial intelligence (AI) in PHY design has cautiously become a trend. A deep neural network (DNN), one of the population techniques of AI, enables the utilization of its ‘learnable’ feature to handle big data and establish a global system model. In this thesis, we exploited this characteristic of DNN as powerful assistance to implement two receiver designs in two different use-cases. We considered a DNN-based joint baseband demodulator and channel decoder (DeModCoder), and a DNN-based joint equalizer, baseband demodulator, and channel decoder (DeTecModCoder) in two single operational blocks, respectively. The multi-label classification (MLC) scheme was equipped to the output of conducted DNN model and hence yielded lower computational complexity than the multiple output classification (MOC) manner. The functional DNN model can be trained offline over a wide range of SNR values under different types of noises, channel fading, etc., and deployed in the real-time application; therefore, the demands of estimation of noise variance and statistical information of underlying noise can be avoided. The simulation performances indicated that compared to the corresponding conventional receiver signal processing schemes, the proposed AI-aided receiver designs have achieved the same bit error rate (BER) with around 3 dB lower SNR

MSAT-X: A technical introduction and status report

A technical introduction and status report for the Mobile Satellite Experiment (MSAT-X) program is presented. The concepts of a Mobile Satellite System (MSS) and its unique challenges are introduced. MSAT-X's role and objectives are delineated with focus on its achievements. An outline of MSS design philosophy is followed by a presentation and analysis of the MSAT-X results, which are cast in a broader context of an MSS. The current phase of MSAT-X has focused notably on the ground segment of MSS. The accomplishments in the four critical technology areas of vehicle antennas, modem and mobile terminal design, speech coding, and networking are presented. A concise evolutionary trace is incorporated in each area to elucidate the rationale leading to the current design choices. The findings in the area of propagation channel modeling are also summarized and their impact on system design discussed. To facilitate the assessment of the MSAT-X results, technology and subsystem recommendations are also included and integrated with a quantitative first-generation MSS design

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

Reduction of perceptual redundancy for data compression of television signals

Imperial Users onl

Transmission of compressed images over power line channel

In the telecommunications industry, the use of existing power lines has drawn the attention of many researchers in the recent years. PLC suffers from impulsive noise that can affect data transmission by causing bit or burst errors. In this thesis, PLC channel was used as a transmission scheme to transmit compressed still images using FFT-OFDM. When lossy compression is applied to an image, a small loss of quality in the compressed image is tolerated. One of the challenging tasks in image compression and transmission is the trade-off between compression ratio and image quality. Therefore, we utilized the latest developments in quality assessment techniques, SSIM, to adaptively optimize this trade-off to the type of image application which the compression is being used for. A comparison between different compression techniques, namely, discrete cosine transform (DCT), discrete wavelet transform (DWT), and block truncation coding (BTC) was carried out. The performance criteria for our compression methods include the compression ratio, relative root-meansquared (RMS) error of the received data, and image quality evaluation via structural similarity index (SSIM). Every link in a powerline has its own attenuation profile depending on the length, layout, and cable types. Also, the influences of multipath fading due to reflections at branching point vary the attenuation profile of the link. As a result, we observed the effect of different parameters of the PLC channel based on the number of paths, and length of link on the quality of the image. Simulations showed that the image quality is highly affected by the interaction of the distance of PLC channel link and the number of multipath reflections. The PLC channel is assumed to be subjected to Gaussian and impulsive noises. There are two types of impulsive noise: asynchronous impulsive noise and periodic impulsive noise synchronous to the mains frequency. BER analysis was performed to compare the performance of the channel for the two types of impulsive noise under three impulsive scenarios. The first scenario is named as "heavily disturbed" and it was measured during the evening hours in a transformer substation in an industrial area. The second scenario is named as "moderately disturbed" and was recorded in a transformer substation in a residential area with detached and terraced houses. The third scenario is named as "weakly disturbed" and was recorded during night-time in an apartment located in a large building. The experiments conducted showed that both types of noise performed similarly in the three impulsive noise scenarios. We implemented Bose-Chaudhuri-Hocquenghen (BCH) coding to study the performance of Power Line Channel (PLC) impaired by impulsive noise and AWGN. BCH codes and RS codes are related and their decoding algorithms are quite similar. A comparison was made between un-coded system and BCH coding system. The performance of the system is assessed by the quality of the image for different sizes of BCH encoder, in three different impulsive environments. Simulation results showed that with BCH coding, the performance of the PLC system has improved dramatically in all three impulsive scenarios