Channel estimation techniques for filter bank multicarrier based transceivers for next generation of wireless networks

A dissertation submitted to Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical and Information Engineering), August 2017The fourth generation (4G) of wireless communication system is designed based on the principles of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) where the cyclic prefix (CP) is used to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) in order to achieve higher data rates in comparison to the previous generations of wireless networks. Various filter bank multicarrier systems have been considered as potential waveforms for the fast emerging next generation (xG) of wireless networks (especially the fifth generation (5G) networks). Some examples of the considered waveforms are orthogonal frequency division multiplexing with offset quadrature amplitude modulation based filter bank, universal filtered multicarrier (UFMC), bi-orthogonal frequency division multiplexing (BFDM) and generalized frequency division multiplexing (GFDM). In perfect reconstruction (PR) or near perfect reconstruction (NPR) filter bank designs, these aforementioned FBMC waveforms adopt the use of well-designed prototype filters (which are used for designing the synthesis and analysis filter banks) so as to either replace or minimize the CP usage of the 4G networks in order to provide higher spectral efficiencies for the overall increment in data rates. The accurate designing of the FIR low-pass prototype filter in NPR filter banks results in minimal signal distortions thus, making the analysis filter bank a time-reversed version of the corresponding synthesis filter bank. However, in non-perfect reconstruction (Non-PR) the analysis filter bank is not directly a time-reversed version of the corresponding synthesis filter bank as the prototype filter impulse response for this system is formulated (in this dissertation) by the introduction of randomly generated errors. Hence, aliasing and amplitude distortions are more prominent for Non-PR. Channel estimation (CE) is used to predict the behaviour of the frequency selective channel and is usually adopted to ensure excellent reconstruction of the transmitted symbols. These techniques can be broadly classified as pilot based, semi-blind and blind channel estimation schemes. In this dissertation, two linear pilot based CE techniques namely the least square (LS) and linear minimum mean square error (LMMSE), and three adaptive channel estimation schemes namely least mean square (LMS), normalized least mean square (NLMS) and recursive least square (RLS) are presented, analyzed and documented. These are implemented while exploiting the near orthogonality properties of offset quadrature amplitude modulation (OQAM) to mitigate the effects of interference for two filter bank waveforms (i.e. OFDM/OQAM and GFDM/OQAM) for the next generation of wireless networks assuming conditions of both NPR and Non-PR in slow and fast frequency selective Rayleigh fading channel. Results obtained from the computer simulations carried out showed that the channel estimation schemes performed better in an NPR filter bank system as compared with Non-PR filter banks. The low performance of Non-PR system is due to the amplitude distortion and aliasing introduced from the random errors generated in the system that is used to design its prototype filters. It can be concluded that RLS, NLMS, LMS, LMMSE and LS channel estimation schemes offered the best normalized mean square error (NMSE) and bit error rate (BER) performances (in decreasing order) for both waveforms assuming both NPR and Non-PR filter banks. Keywords: Channel estimation, Filter bank, OFDM/OQAM, GFDM/OQAM, NPR, Non-PR, 5G, Frequency selective channel.CK201

MC-DS-CDMA System based on DWT and STBC in ITU Multipath Fading Channels Model

 في هذه الورقة، تم تحسين أداء النفوذ المتعدد بالتقسيم لرمز السلسلة المباشر متعدد الموجات (MC-DS-CDMA) في تطبيقات MC-DS-CDMA الثابتة والتطبيقات MC-DS-CDMA  المتنقلة باستعمال تعويضات التشفير الزمنية الفضائية وتحويل فورير السريعة المنفصلة (FFT) أو تحويل المويجات المنفصلة DWT. وقد تمت محاكاة أنظمة MC-DS-CDMA  باستخدام ماتلاب 2015a. من خلال محاكاة النظام المقترح، يمكن تغيير المعالم المختلفة واختبارها. ويتم الحصول على معدل خطأ البيانات (BER) لهذه الأنظمة على مدى واسع من نسبة الإشارة إلى الضوضاء. وقد قورنت جميع نتائج المحاكاة مع بعضها البعض باستخدام حجم الموجة الحاملة الفرعية المختلفة FFT أو DWT مع ل STBC 1،2،3 و 4 هوائيات في المرسل وفي مختلف قنوات الخبو في متعددة الممرات ITU ومختلف ترددات دوبلر (fd).In this paper, the performance of multicarrier direct sequence code division multiple access (MC-DS-CDMA) in fixed MC-DS-CDMA and Mobile MC-DS-CDMA applications have been improved by using the compensations of space time block coding and Discrete Fast Fourier transforms (FFT) or Discrete Wavelets transform DWT. These MC-DS-CDMA systems had been simulated using MATLAB 2015a. Through simulation of the proposed system, various parameters can be changed and tested. The Bit Error Rate (BERs) of these systems are obtained over wide range of signal to noise ratio. All simulation results had been compared with each other using different subcarrier size of FFT or DWT with STBC for 1,2,3 and 4 antennas in transmitter and under different ITU multipath fading channels and different Doppler frequencies (fd). The proposed structures of STBC-MC-DS-CDMA system based on (DWT) batter than based on (FFT) in varies Doppler frequencies and subcarrier size. Also, proposed system with STBC based on 4 transmitters better than other systems based on 1 or 2 or 3 transmitters in all Doppler frequencies and subcarrier size in all simulation results

D3.2 First performance results for multi -node/multi -antenna transmission technologies

This deliverable describes the current results of the multi-node/multi-antenna technologies investigated within METIS and analyses the interactions within and outside Work Package 3. Furthermore, it identifies the most promising technologies based on the current state of obtained results. This document provides a brief overview of the results in its first part. The second part, namely the Appendix, further details the results, describes the simulation alignment efforts conducted in the Work Package and the interaction of the Test Cases. The results described here show that the investigations conducted in Work Package 3 are maturing resulting in valuable innovative solutions for future 5G systems.Fantini. R.; Santos, A.; De Carvalho, E.; Rajatheva, N.; Popovski, P.; Baracca, P.; Aziz, D.... (2014). D3.2 First performance results for multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675

Rate adaptive resource allocation with fairness control for OFDMA networks

The use of opportunistic radio resource allocation techniques in order to efficiently manage the resources generates a low fairness among the users in a cellular system due to uneven Quality of Service (QoS) distribution. Some classic rate adaptive policies tried to tackle this problem for OFDMA systems by proposing solutions to maximize capacity, maximize fairness, or find a static trade-off between these two objectives. This work generalizes these classic policies and propose a dynamic fairness/rate adaptive technique based on dynamic sub-carrier assignment and equal power allocation that considers a new fairness constraint in the optimization problem. By means of extensive system-level simulations, it is demonstrated that the proposed technique is able to provide an instantaneous (short-term) fairness control, which provides to the network operator the flexibility to operate on any desired trade-off point.Peer ReviewedPostprint (published version

Multi-set space-time shift keying and space-frequency space-time shift keying for millimeter-wave communications

In this paper, we introduce a novel OFDM-aided multifunctional multiple-input multiple-output scheme based on multi-set space-time shift keying (MS-STSK), where the information transmitted over each subcarrier is divided into two parts: STSK codeword and the implicit antenna combination (AC) index. In MS-STSK, a unique combination of antennas can be activated at each subcarrier to convey extra information over the AC index while additionally transmitting the STSK codeword. Furthermore, inspired by the MS-STSK concept, this scheme is extended also to the frequency domain in the novel context of our multi-space-frequency STSK (MSF-STSK), where the total number of subcarriers is partitioned into blocks to implicitly carry the block's frequency index. The proposed MSF-STSK scheme benefits from the huge bandwidths available at mmWaves for partitioning the total number of OFDM subcarriers into blocks to convey more information over the frequency domain. Both proposed systems use STSK codewords as the basic transmission block, and they can achieve higher data throughput and better BER performance than STSK. Moreover, given that the system is meant to operate at mmWaves, antenna arrays relying on several antenna elements are employed at both the transmitter and receiver for analogue beamforming with the aid of phase shifters and power amplifiers to overcome the effect of high path loss

On Efficient Signal Processing Algorithms for Signal Detection and PAPR Reduction in OFDM Systems

The driving force of the study is susceptibility of LS algorithm to noise. As LS algorithm is simple to implement, hence it’s performance improvement can contribute a lot to the wireless technology that are especially deals with high computation. Cascading of AdaBoost algorithm with LS greatly influences the OFDM system performance. Performance of Adaptive Boosting based symbol recovery was investigated on the performance of LS, MMSE, BLUE were also compared with the performance of AdaBoost algorithm and MMSE has been found the higher computational complexity. Furthermore, MMSE also requires apriori channel statistics and computational complexity O(5N3) of the MMSE increases exponentially as the number of carrier increases. For the Adaboost case the computational complexity calculation is little different.Therefore, in the training stage of the AdaBoost algorithm, the computational complexity is only O(nT M) Furthermore, as it is a classification algorithm so in the receiver side we will require a separate de-mapper (or decoder) to get the desired data bits, i.e., a. SAS aided DCT based PAPR reduction 1326 and b. SAS aided DCT based PAPR reduction. A successive addition subtraction preprocessed DCT based PAPR reduction technique was proposed. Here, the performance of proposed method was compared with other preexisting techniques like SLM and PTS and the performance of the proposed method was seen to outperform specially in low PAPR region. In the proposed PAPR reduction method, the receiver is aware of the transmitted signal processing, this enables a reverse operation at the receiver to extract the transmit data. Hence the requirement of sending extra information through extra subcarrier is eliminated. The proposed method is also seen to be spectrally efficient. In the case of PTS and SLM it is inevitable to send the side information to retrieve the transmit signal. Hence, these two methods are spectrally inefficient. Successive addition subtraction based PAPR reduction method was also applied to MIMO systems. The performance of the SAS based PAPR reduction method also showed better performance as compared to other technique. An extensive simulation of MIMO OFDM PAPR reduction was carried out by varying the number of subcarriers and number of transmitter antennas. A detailed computational complexity analysis was also carried out. BATE aided SDMA multi user detection. A detailed study of SDMA system was carried out with it’s mathematical analysis.Many linear and non linear detectors like ML, MMSE, PIC, SIC have been proposed in literature for multiuser detection of SDMA system. However, except MMSE every receivers other are computational extensive. So as to enhance the performance of the MMSE MUD a meta heuristic Bat algorithm was incorporated in cascade with MMSE

Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e ComputadoresThe forthcoming generation of mobile communications, 5G, will settle a new standard for a larger bandwidth and better Quality of Service (QoS). With the exploding growth rate of user generated data, wireless standards must cope with this growth and at the same time be energy efficient to avoid depleting the batteries of wireless devices. Besides these issues, in a broadband wireless setting QoS can be severely affected from a multipath dispersive channel and therefore be energy demanding. Cross-layered architectures are a good choice to enhance the overall performance of a wireless system. Examples of cross-layered Physical (PHY) - Medium Access Control (MAC) architectures are type-II Diversity Combining (DC) Hybrid-ARQ (H-ARQ) and Multi-user Detection (MUD) schemes. Cross-layered type-II DC H-ARQ schemes reuse failed packet transmissions to enhance data reception on posterior retransmissions; MUD schemes reuse data information from previously collided packets on posterior retransmissions to enhance data reception. For a multipath dispersive channel, a PHY layer analytical model is proposed for Single-Carrier with Frequency Domain Equalization (SC-FDE) that supports DC H-ARQ and MUD. Based on this analytical model, three PHY-MAC protocols are proposed. A crosslayered Time Division Multiple Access (TDMA) scheme that uses DC H-ARQ is modeled and its performance is studied in this document; the performance analysis shows that the scheme performs better with DC and achieves a better energy efficiency at the cost of a higher delay. A novel cross-layered prefix-assisted Direct-Sequence Code Division Multiple Access (DS-CDMA) scheme is proposed and modeled in this document, it uses principles of DC and MUD. This protocol performs better by means of additional retransmissions, achieving better energy efficiency, at the cost of higher redundancy from a code spreading gain. Finally, a novel cross-layered protocol H-ARQ Network Division Multiple Access (H-NDMA) is proposed and modeled, where the combination of DC H-ARQ and MUD is used with the intent of maximizing the system capacity with a lower delay; system results show that the proposed scheme achieves better energy efficiency and a better performance at the cost of a higher number of retransmissions. A comparison of the three cross-layered protocols is made, using the PHY analytical model, under normalized conditions using the same amount of maximum redundancy. Results show that the H-NDMA protocol, in general, obtains the best results, achieving a good performance and a good energy efficiency for a high channel load and low Signal-to-Noise Ratio (SNR). TDMA with DC H-ARQ achieves the best energy efficiency, although presenting the worst delay. Prefix-assisted DS-CDMA in the other hand shows good delay results but presents the worst throughput and energy efficiency

Near-capacity fixed-rate and rateless channel code constructions

Fixed-rate and rateless channel code constructions are designed for satisfying conflicting design tradeoffs, leading to codes that benefit from practical implementations, whilst offering a good bit error ratio (BER) and block error ratio (BLER) performance. More explicitly, two novel low-density parity-check code (LDPC) constructions are proposed; the first construction constitutes a family of quasi-cyclic protograph LDPC codes, which has a Vandermonde-like parity-check matrix (PCM). The second construction constitutes a specific class of protograph LDPC codes, which are termed as multilevel structured (MLS) LDPC codes. These codes possess a PCM construction that allows the coexistence of both pseudo-randomness as well as a structure requiring a reduced memory. More importantly, it is also demonstrated that these benefits accrue without any compromise in the attainable BER/BLER performance. We also present the novel concept of separating multiple users by means of user-specific channel codes, which is referred to as channel code division multiple access (CCDMA), and provide an example based on MLS LDPC codes. In particular, we circumvent the difficulty of having potentially high memory requirements, while ensuring that each user’s bits in the CCDMA system are equally protected. With regards to rateless channel coding, we propose a novel family of codes, which we refer to as reconfigurable rateless codes, that are capable of not only varying their code-rate but also to adaptively modify their encoding/decoding strategy according to the near-instantaneous channel conditions. We demonstrate that the proposed reconfigurable rateless codes are capable of shaping their own degree distribution according to the nearinstantaneous requirements imposed by the channel, but without any explicit channel knowledge at the transmitter. Additionally, a generalised transmit preprocessing aided closed-loop downlink multiple-input multiple-output (MIMO) system is presented, in which both the channel coding components as well as the linear transmit precoder exploit the knowledge of the channel state information (CSI). More explicitly, we embed a rateless code in a MIMO transmit preprocessing scheme, in order to attain near-capacity performance across a wide range of channel signal-to-ratios (SNRs), rather than only at a specific SNR. The performance of our scheme is further enhanced with the aid of a technique, referred to as pilot symbol assisted rateless (PSAR) coding, whereby a predetermined fraction of pilot bits is appropriately interspersed with the original information bits at the channel coding stage, instead of multiplexing pilots at the modulation stage, as in classic pilot symbol assisted modulation (PSAM). We subsequently demonstrate that the PSAR code-aided transmit preprocessing scheme succeeds in gleaning more information from the inserted pilots than the classic PSAM technique, because the pilot bits are not only useful for sounding the channel at the receiver but also beneficial for significantly reducing the computational complexity of the rateless channel decoder

Spatial diversity in MIMO communication systems with distributed or co-located antennas

The use of multiple antennas in wireless communication systems has gained much attention during the last decade. It was shown that such multiple-input multiple-output (MIMO) systems offer huge advantages over single-antenna systems. Typically, quite restrictive assumptions are made concerning the spacing of the individual antenna elements. On the one hand, it is typically assumed that the antenna elements at transmitter and receiver are co-located, i.e., they belong to some sort of antenna array. On the other hand, it is often assumed that the antenna spacings are sufficiently large, so as to justify the assumption of independent fading. In this thesis, the above assumptions are relaxed. In the first part, it is shown that MIMO systems with distributed antennas and MIMO systems with co-located antennas can be treated in a single, unifying framework. In the second part this fact is utilized, in order to develop appropriate transmit power allocation strategies for co-located and distributed MIMO systems. Finally, the third part focuses on specific synchronization problems that are of interest for distributed MIMO systems

Learning-based communication system design – autoencoder for (differential) block coded modulation designs and path loss predictions

Shannon’s channel coding theorem states the existence of long random codes that can make the error probability arbitrarily small. Recently, advanced error-correcting codes such as turbo and low-density parity-check codes have almost reached the theoretical Shannon limit for binary additive white Gaussian noise channels. However, designing optimal high-rate short-block codes with automatic bit-labeling for various wireless networks is still an unsolved problem. Deep-learning-based autoencoders (AE) have appeared as a potential near-optimal solution for designing wireless communications systems. We take a holistic approach that jointly optimizes all the components of the communication networks by performing data-driven end-to-end learning of the neural network-based transmitter and receiver together. Specifically, to tackle the fading channels, we show that AE frameworks can perform near-optimal block coded-modulation (BCM) and differential BCM (d-BCM) designs in the presence and absence of the channel state information knowledge. Moreover, we focus on AE-based designing of high-rate short block codes with automatic bit-labeling that are capable of outperforming conventional networks with larger margins as the rate R increases. We also investigate the BCM and d-BCM from an information-theoretic perspective. With the advent of internet-of-things (IoT) networks and the widespread use of small devices, we face the challenge of limited available bandwidth. Therefore, novel techniques need to be utilized, such as full-duplex (FD) mode transmission reception at the base station for the full utilization of the spectrum, and non-orthogonal multiple access (NOMA) at the user-end for serving multiple IoT devices while fulfilling their quality-of-service requirement. Furthermore, the deployment of relay nodes will play a pivotal role in improving network coverage, reliability, and spectral efficiency for the future 5G networks. Thus, we design and develop novel end-to-end-learning-based AE frameworks for BCM and d-BCM in various scenarios such as amplify-and-forward and decode-and-forward relaying networks, FD relaying networks, and multi-user downlink networks. We focus on interpretability and understand the AE-based BCM and d-BCM from an information-theoretic perspective, such as the AE’s estimated mutual information, convergence, loss optimization, and training principles. We also determine the distinct properties of AE-based (differential) coded-modulation designs in higher-dimensional space. Moreover, we also studied the reproducibility of the trained AE framework. In contrast, large bandwidth and worldwide spectrum availability at mm-wave bands have also shown a great potential for 5G and beyond, but the high path loss (PL) and significant scattering/absorption loss make the signal propagation challenging. Highly accurate PL prediction is fundamental for mm-wave network planning and optimization, whereas existing methods such as slope-intercept models and ray tracing fall short in capturing the large street-by-street variation seen in urban cities. We also exploited the potential benefits of AE framework-based compression capabilities in mm-wave PL prediction. Specifically, we employ extensive 28 GHz measurements from Manhattan Street canyons and model the street clutters via a LiDAR point cloud dataset and 3D-buildings by a mesh-grid building dataset. We aggressively compress 3D-building shape information using convolutional-AE frameworks to reduce overfitting and propose a machine learning (ML)-based PL prediction model for mm-wave propagation.EPSRC-UKRI fundin