Feedforward data-aided phase noise estimation from a DCT basis expansion

This contribution deals with phase noise estimation from pilot symbols. The phase noise process is approximated by an expansion of discrete cosine transform (DCT) basis functions containing only a few terms. We propose a feedforward algorithm that estimates the DCT coefficients without requiring detailed knowledge about the phase noise statistics. We demonstrate that the resulting (linearized) mean-square phase estimation error consists of two contributions: a contribution from the additive noise, that equals the Cramer-Rao lower bound, and a noise independent contribution, that results front the phase noise modeling error. We investigate the effect of the symbol sequence length, the pilot symbol positions, the number of pilot symbols, and the number of estimated DCT coefficients it the estimation accuracy and on the corresponding bit error rate (PER). We propose a pilot symbol configuration allowing to estimate any number of DCT coefficients not exceeding the number of pilot Symbols, providing a considerable Performance improvement as compared to other pilot symbol configurations. For large block sizes, the DCT-based estimation algorithm substantially outperforms algorithms that estimate only the time-average or the linear trend of the carrier phase. Copyright (C) 2009 J. Bhatti and M. Moeneclaey

Coherent Optical OFDM Modem Employing Artificial Neural Networks for Dispersion and Nonlinearity Compensation in a Long-Haul Transmission System

In order to satisfy the ever increasing demand for the bandwidth requirement in broadband services the optical orthogonal frequency division multiplexing (OOFDM) scheme is being considered as a promising technique for future high-capacity optical networks. The aim of this thesis is to investigate, theoretically, the feasibility of implementing the coherent optical OFDM (CO-OOFDM) technique in long haul transmission networks. For CO-OOFDM and Fast-OFDM systems a set of modulation formats dependent analogue to digital converter (ADC) clipping ratio and the quantization bit have been identified, moreover, CO-OOFDM is more resilient to the chromatic dispersion (CD) when compared to the bandwidth efficient Fast-OFDM scheme. For CO-OOFDM systems numerical simulations are undertaken to investigate the effect of the number of sub-carriers, the cyclic prefix (CP), and ADC associated parameters such as the sampling speed, the clipping ratio, and the quantisation bit on the system performance over single mode fibre (SMF) links for data rates up to 80 Gb/s. The use of a large number of sub-carriers is more effective in combating the fibre CD compared to employing a long CP. Moreover, in the presence of fibre non-linearities identifying the optimum number of sub-carriers is a crucial factor in determining the modem performance. For a range of signal data rates up to 40 Gb/s, a set of data rate and transmission distance-dependent optimum ADC parameters are identified in this work. These parameters give rise to a negligible clipping and quantisation noise, moreover, ADC sampling speed can increase the dispersion tolerance while transmitting over SMF links. In addition, simulation results show that the use of adaptive modulation schemes improves the spectrum usage efficiency, thus resulting in higher tolerance to the CD when compared to the case where identical modulation formats are adopted across all sub-carriers. For a given transmission distance utilizing an artificial neural networks (ANN) equalizer improves the system bit error rate (BER) performance by a factor of 50% and 70%, respectively when considering SMF firstly CD and secondly nonlinear effects with CD. Moreover, for a fixed BER of 10-3 utilizing ANN increases the transmission distance by 1.87 times and 2 times, respectively while considering SMF CD and nonlinear effects. The proposed ANN equalizer performs more efficiently in combating SMF non-linearities than the previously published Kerr nonlinearity electrical compensation technique by a factor of 7

System capacity enhancement for 5G network and beyond

A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Doctor of PhilosophyThe demand for wireless digital data is dramatically increasing year over year. Wireless communication systems like Laptops, Smart phones, Tablets, Smart watch, Virtual Reality devices and so on are becoming an important part of people’s daily life. The number of mobile devices is increasing at a very fast speed as well as the requirements for mobile devices such as super high-resolution image/video, fast download speed, very short latency and high reliability, which raise challenges to the existing wireless communication networks. Unlike the previous four generation communication networks, the fifth-generation (5G) wireless communication network includes many technologies such as millimetre-wave communication, massive multiple-input multiple-output (MIMO), visual light communication (VLC), heterogeneous network (HetNet) and so forth. Although 5G has not been standardised yet, these above technologies have been studied in both academia and industry and the goal of the research is to enhance and improve the system capacity for 5G networks and beyond by studying some key problems and providing some effective solutions existing in the above technologies from system implementation and hardware impairments’ perspective. The key problems studied in this thesis include interference cancellation in HetNet, impairments calibration for massive MIMO, channel state estimation for VLC, and low latency parallel Turbo decoding technique. Firstly, inter-cell interference in HetNet is studied and a cell specific reference signal (CRS) interference cancellation method is proposed to mitigate the performance degrade in enhanced inter-cell interference coordination (eICIC). This method takes carrier frequency offset (CFO) and timing offset (TO) of the user’s received signal into account. By reconstructing the interfering signal and cancelling it afterwards, the capacity of HetNet is enhanced. Secondly, for massive MIMO systems, the radio frequency (RF) impairments of the hardware will degrade the beamforming performance. When operated in time duplex division (TDD) mode, a massive MIMO system relies on the reciprocity of the channel which can be broken by the transmitter and receiver RF impairments. Impairments calibration has been studied and a closed-loop reciprocity calibration method is proposed in this thesis. A test device (TD) is introduced in this calibration method that can estimate the transmitters’ impairments over-the-air and feed the results back to the base station via the Internet. The uplink pilots sent by the TD can assist the BS receivers’ impairment estimation. With both the uplink and downlink impairments estimates, the reciprocity calibration coefficients can be obtained. By computer simulation and lab experiment, the performance of the proposed method is evaluated. Channel coding is an essential part of a wireless communication system which helps fight with noise and get correct information delivery. Turbo codes is one of the most reliable codes that has been used in many standards such as WiMAX and LTE. However, the decoding process of turbo codes is time-consuming and the decoding latency should be improved to meet the requirement of the future network. A reverse interleave address generator is proposed that can reduce the decoding time and a low latency parallel turbo decoder has been implemented on a FPGA platform. The simulation and experiment results prove the effectiveness of the address generator and show that there is a trade-off between latency and throughput with a limited hardware resource. Apart from the above contributions, this thesis also investigated multi-user precoding for MIMO VLC systems. As a green and secure technology, VLC is achieving more and more attention and could become a part of 5G network especially for indoor communication. For indoor scenario, the MIMO VLC channel could be easily ill-conditioned. Hence, it is important to study the impact of the channel state to the precoding performance. A channel state estimation method is proposed based on the signal to interference noise ratio (SINR) of the users’ received signal. Simulation results show that it can enhance the capacity of the indoor MIMO VLC system

Low-Complexity Algorithms for Channel Estimation in Optimised Pilot-Assisted Wireless OFDM Systems

Orthogonal frequency division multiplexing (OFDM) has recently become a dominant transmission technology considered for the next generation fixed and mobile broadband wireless communication systems. OFDM has an advantage of lessening the severe effects of the frequency-selective (multipath) fading due to the band splitting into relatively flat fading subchannels, and allows for low-complexity transceiver implementation based on the fast Fourier transform algorithms. Combining OFDM modulation with multilevel frequency-domain symbol mapping (e.g., QAM) and spatial multiplexing (SM) over the multiple-input multiple-output (MIMO) channels, can theoretically achieve near Shannon capacity of the communication link. However, the high-rate and spectrumefficient system implementation requires coherent detection at the receiving end that is possible only when accurate channel state information (CSI) is available. Since in practice, the response of the wireless channel is unknown and is subject to random variation with time, the receiver typically employs a channel estimator for CSI acquisition. The channel response information retrieved by the estimator is then used by the data detector and can also be fed back to the transmitter by means of in-band or out-of-band signalling, so the latter could adapt power loading, modulation and coding parameters according to the channel conditions. Thus, design of an accurate and robust channel estimator is a crucial requirement for reliable communication through the channel, which is selective in time and frequency. In a MIMO configuration, a separate channel estimator has to be associated with each transmit/receive antenna pair, making the estimation algorithm complexity a primary concern. Pilot-assisted methods, relying on the insertion of reference symbols in certain frequencies and time slots, have been found attractive for identification of the doubly-selective radio channels from both the complexity and performance standpoint. In this dissertation, a family of the reduced-complexity estimators for the single and multiple-antenna OFDM systems is developed. The estimators are based on the transform-domain processing and have the same order of computational complexity, irrespective of the number of pilot subcarriers and their positioning. The common estimator structure represents a cascade of successive small-dimension filtering modules. The number of modules, as well as their order inside the cascade, is determined by the class of the estimator (one or two-dimensional) and availability of the channel statistics (correlation and signal-to-noise power ratio). For fine precision estimation in the multipath channels with statistics not known a priori, we propose recursive design of the filtering modules. Simulation results show that in the steady state, performance of the recursive estimators approaches that of their theoretical counterparts, which are optimal in the minimum mean square error (MMSE) sense. In contrast to the majority of the channel estimators developed so far, our modular-type architectures are suitable for the reconfigurable OFDM transceivers where the actual channel conditions influence the decision of what class of filtering algorithm to use, and how to allot pilot subcarrier positions in the band. In the pilot-assisted transmissions, channel estimation and detection are performed separately from each other over the distinct subcarrier sets. The estimator output is used only to construct the detector transform, but not as the detector input. Since performance of both channel estimation and detection depends on the signal-to-noise power vi ratio (SNR) at the corresponding subcarriers, there is a dilemma of the optimal power allocation between the data and the pilot symbols as these are conflicting requirements under the total transmit power constraint. The problem is exacerbated by the variety of channel estimators. Each kind of estimation algorithm is characterised by its own SNR gain, which in general can vary depending on the channel correlation. In this dissertation, we optimise pilot-data power allocation for the case of developed low-complexity one and two-dimensional MMSE channel estimators. The resultant contribution is manifested by the closed-form analytical expressions of the upper bound (suboptimal approximate value) on the optimal pilot-to-data power ratio (PDR) as a function of a number of design parameters (number of subcarriers, number of pilots, number of transmit antennas, effective order of the channel model, maximum Doppler shift, SNR, etc.). The resultant PDR equations can be applied to the MIMO-OFDM systems with arbitrary arrangement of the pilot subcarriers, operating in an arbitrary multipath fading channel. These properties and relatively simple functional representation of the derived analytical PDR expressions are designated to alleviate the challenging task of on-the-fly optimisation of the adaptive SM-MIMO-OFDM system, which is capable of adjusting transmit signal configuration (e.g., block length, number of pilot subcarriers or antennas) according to the established channel conditions

Enabling Technology in Optical Fiber Communications: From Device, System to Networking

This book explores the enabling technology in optical fiber communications. It focuses on the state-of-the-art advances from fundamental theories, devices, and subsystems to networking applications as well as future perspectives of optical fiber communications. The topics cover include integrated photonics, fiber optics, fiber and free-space optical communications, and optical networking

SoftCast: Clean-slate Scalable Wireless Video

Video broadcast and mobile video challenge the conventional wireless design. In broadcast and mobile scenarios the bit rate supported by the channel differs across receivers and varies quickly over time. The conventional design however forces the source to pick a single bit rate and degrades sharply when the channel cannot not support the chosen bit rate. This paper presents SoftCast, a clean-slate design for wireless video where the source transmits one video stream that each receiver decodes to a video quality commensurate with its specific instantaneous channel quality. To do so, SoftCast ensures the samples of the digital video signal transmitted on the channel are linearly related to the pixels' luminance. Thus, when channel noise perturbs the transmitted signal samples, the perturbation naturally translates into approximation in the original video pixels. Hence, a receiver with a good channel (low noise) obtains a high fidelity video, and a receiver with a bad channel (high noise) obtains a low fidelity video. We implement SoftCast using the GNURadio software and the USRP platform. Results from a 20-node testbed show that SoftCast improves the average video quality (i.e., PSNR) across broadcast receivers in our testbed by up to 5.5dB. Even for a single receiver, it eliminates video glitches caused by mobility and increases robustness to packet loss by an order of magnitude

OFDM techniques for multimedia data transmission

Orthogonal Frequency Division Multiplexing (OFDM) is an efficient parallel data transmission scheme that has relatively recently become popular in both wired and wireless communication systems for the transmission of multimedia data. OFDM can be found at the core of well known systems such as digital television/radio broadcasting, ADSL internet and wireless LANs. Research into the OFDM field continually looks at different techniques to attempt to make this type of transmission more efficient. More recent works in this area have considered the benefits of using wavelet transforms in place of the Fourier transforms traditionally used in OFDM systems and other works have looked at data compression as a method of increasing throughput in these types of transmission systems. The work presented in this thesis considers the transmission of image and video data in traditional OFDM transmission and discusses the strengths and weaknesses of this method. This thesis also proposes a new type of OFDM system that combines transmission and data compression into one block. By merging these two processes into one the complexity of the system is reduced, therefore promising to increase system efficiency. The results presented in this thesis show the novel compressive OFDM method performs well in channels with a low signal-to-noise ratio. Comparisons with traditional OFDM with lossy compression show a large improvement in the quality of the data received with the new system when used in these noisy channel environments. The results also show superior results are obtained when transmitting image and video data using the new method, the high correlative properties of images are ideal for effective transmission using the new technique. The new transmission technique proposed in this thesis also gives good results when considering computation time. When compared to MATLAB simulations of a traditional DFT-based OFDM system with a separate compression block, the proposed transmission method was able to reduce the computation time by between a half to three-quarters. This decrease in computational complexity also contributes to transmission efficiency when considering the new method

Reduced-complexity signal processing techniques for multiple-input multiple-output storage and wireless communication systems

Ph.DNUS-TU/E JOINT PH.D. PROGRAMM