Superimposed training for single carrier transmission in future mobile communications

The amount of wireless devices and wireless traffic has been increasing exponentially for the last ten years. It is forecasted that the exponential growth will continue without saturation till 2020 and probably further. So far, network vendors and operators have tackled the problem by introducing new evolutions of cellular macro networks, where each evolution has increased the physical layer spectral efficiency. Unfortunately, the spectral efficiency of the physical layer is achieving the Shannon-Hartley limit and does not provide much room for improvement anymore. However, considering the overhead due to synchronization and channel estimation reference symbols in the context of physical layer spectral efficiency, we believe that there is room for improvement. In this thesis, we will study the potentiality of superimposed training methods, especially data-dependent superimposed training, to boost the spectral efficiency of wideband single carrier communications even further. The main idea is that with superimposed training we can transmit more data symbols in the same time duration as compared to traditional time domain multiplexed training. In theory, more data symbols means more data bits which indicates higher throughput for the end user. In practice, nothing is free. With superimposed training we encounter self-interference between the training signal and the data signal. Therefore, we have to look for iterative receiver structures to separate these two or to estimate both, the desired data signal and the interfering component. In this thesis, we initiate the studies to find out if we truly can improve the existing systems by introducing the superimposed training scheme. We show that in certain scenarios we can achieve higher spectral efficiency, which maps directly to higher user throughput, but with the cost of higher signal processing burden in the receiver. In addition, we provide analytical tools for estimating the symbol or bit error ratio in the receiver with a given parametrization. The discussion leads us to the conclusion that there still remains several open topics for further study when looking for new ways of optimizing the overhead of reference symbols in wireless communications. Superimposed training with data-dependent components may prove to provide extra throughput gain. Furthermore, the superimposed component may be used for, e.g., improved synchronization, low bit-rate signaling or continuous tracking of neighbor cells. We believe that the current systems could be improved by using the superimposed training collectively with time domain multiplexed training

Joint detection and channel estimation for MIMO systems with SC-FDE modulations

SC modulation (Single-Carrier) with FDE (Frequency-Domain Equalization) allows excellent performance in severely time-dispersive channels, provided that accurate channel estimates are available at the receiver. For this purpose, pilot symbols and/or training sequences are usually multiplexed with data symbols, which lead to spectral degradation. As an alternative, we can use implicit pilots (i.e., pilots superimposed to data). In this paper we consider MIMO SC-FDE systems where the channel estimation is based on either explicit or implicit pilots, for comparison purposes. An iterative receiver with joint equalization, turbo decoding and channel estimation was employed for optimum results, and to reduce the high interference levels between data and pilots (for the implicit pilots). The main differences between the different schemes are discussed and the performance results show that the use of the proposed techniques for channel estimation yield excellent results.info:eu-repo/semantics/acceptedVersio

Simultaneous Wireless Information and Power Transfer in 5G communication

Green communication technology is expected to be widely adopted in future generation networks to improve energy efficiency and reliability of wireless communication network. Among the green communication technologies,simultaneous wireless information and power transfer (SWIPT) is adopted for its flexible energy harvesting technology through the radio frequency (RF) signa lthati sused for information transmission. Even though existing SWIPT techniques are flexible and adoptable for the wireless communication networks, the power and time resources of the signal need to be shared between infor- mation transmission and RF energy harvesting, and this compromises the quality of the signal. Therefore,SWIP Ttechniques need to be designed to allow an efficient resource allocation for communication and energy harvesting. The goal oft his thesisis to design SWIP Ttechniques that allow efficient,reliable and secure joint communications and power transference. A problem associated to SWIPT techniques combined with multi carrier signals is that the increased power requirements inherent to energy harvesting purposes can exacerbate nonlinear distortion effects at the transmitter. Therefore, we evaluate nonlinear distortion and present feasible solutions to mitigate the impact of nonlinear distortion effects on the performance.Another goal of the thesisis to take advantage of the energy harvesting signals in SWIP Ttechniques for channel estimation and security purposes.Theperformance of these SWIPT techniques is evaluated analytically, and those results are validated by simulations. It is shownthatthe proposed SWIPT schemes can have excellent performance, out performing conventional SWIPT schemes.Espera-se que aschamadas tecnologiasde green communications sejam amplamente ado- tadas em futuras redes de comunicação sem fios para melhorar a sua eficiência energética a fiabilidade.Entre estas,encontram-se as tecnologias SWIPT (Simultaneous Wireless Information and Power Transference), nas quais um sinal radio é usado para transferir simultaneamente potência e informações.Embora as técnicas SWIPT existentes sejam fle- xíveis e adequadas para as redes de comunicações sem fios, os recursos de energia e tempo do sinal precisam ser compartilhados entre a transmissão de informações e de energia, o que pode comprometer a qualidade do sinal. Deste modo,as técnicas SWIPT precisam ser projetadas para permitir uma alocação eficiente de recursos para comunicação e recolha de energia. O objetivo desta tese é desenvolver técnicas SWIPT que permitam transferência de energia e comunicações eficientes,fiáveis e seguras.Um problema associado às técnicas SWIPT combinadas com sinais multi-portadora são as dificuldades de amplificação ine- rentes à combinação de sinais de transmissão de energia com sinais de transferência de dados, que podem exacerbar os efeitos de distorção não-linear nos sinais transmitidos. Deste modo, um dos objectivos desta tese é avaliar o impacto da distorção não-linear em sinais SWIPT, e apresentar soluções viáveis para mitigar os efeitos da distorção não-linear no desempenho da transmissão de dados.Outro objetivo da tese é aproveitar as vantagens dos sinais de transferência de energia em técnicas SWIPT para efeitos de estimação de canal e segurança na comunicação.Os desempenhos dessas técnicas SWIPT são avaliados analiticamente,sendo os respectivos resultados validados por simulações.É mostrado que os esquemas SWIPT propostos podem ter excelente desempenho, superando esquemas SWIPT convencionais

Visible Light Communication (VLC)

Visible light communication (VLC) using light-emitting diodes (LEDs) or laser diodes (LDs) has been envisioned as one of the key enabling technologies for 6G and Internet of Things (IoT) systems, owing to its appealing advantages, including abundant and unregulated spectrum resources, no electromagnetic interference (EMI) radiation and high security. However, despite its many advantages, VLC faces several technical challenges, such as the limited bandwidth and severe nonlinearity of opto-electronic devices, link blockage and user mobility. Therefore, significant efforts are needed from the global VLC community to develop VLC technology further. This Special Issue, “Visible Light Communication (VLC)”, provides an opportunity for global researchers to share their new ideas and cutting-edge techniques to address the above-mentioned challenges. The 16 papers published in this Special Issue represent the fascinating progress of VLC in various contexts, including general indoor and underwater scenarios, and the emerging application of machine learning/artificial intelligence (ML/AI) techniques in VLC

Analysis and Design of Non-Orthogonal Multiple Access (NOMA) Techniques for Next Generation Wireless Communication Systems

The current surge in wireless connectivity, anticipated to amplify significantly in future wireless technologies, brings a new wave of users. Given the impracticality of an endlessly expanding bandwidth, there’s a pressing need for communication techniques that efficiently serve this burgeoning user base with limited resources. Multiple Access (MA) techniques, notably Orthogonal Multiple Access (OMA), have long addressed bandwidth constraints. However, with escalating user numbers, OMA’s orthogonality becomes limiting for emerging wireless technologies. Non-Orthogonal Multiple Access (NOMA), employing superposition coding, serves more users within the same bandwidth as OMA by allocating different power levels to users whose signals can then be detected using the gap between them, thus offering superior spectral efficiency and massive connectivity. This thesis examines the integration of NOMA techniques with cooperative relaying, EXtrinsic Information Transfer (EXIT) chart analysis, and deep learning for enhancing 6G and beyond communication systems. The adopted methodology aims to optimize the systems’ performance, spanning from bit-error rate (BER) versus signal to noise ratio (SNR) to overall system efficiency and data rates. The primary focus of this thesis is the investigation of the integration of NOMA with cooperative relaying, EXIT chart analysis, and deep learning techniques. In the cooperative relaying context, NOMA notably improved diversity gains, thereby proving the superiority of combining NOMA with cooperative relaying over just NOMA. With EXIT chart analysis, NOMA achieved low BER at mid-range SNR as well as achieved optimal user fairness in the power allocation stage. Additionally, employing a trained neural network enhanced signal detection for NOMA in the deep learning scenario, thereby producing a simpler signal detection for NOMA which addresses NOMAs’ complex receiver problem

Interference Suppression in Massive MIMO VLC Systems

The focus of this dissertation is on the development and evaluation of methods and principles to mitigate interference in multiuser visible light communication (VLC) systems using several transmitters. All components of such a massive multiple-input multiple-output (MIMO) system are considered and transformed into a communication system model, while also paying particular attention to the hardware requirements of different modulation schemes. By analyzing all steps in the communication process, the inter-channel interference between users is identified as the most critical aspect. Several methods of suppressing this kind of interference, i.e. to split the MIMO channel into parallel single channels, are discussed, and a novel active LCD-based interference suppression principle at the receiver side is introduced as main aspect of this work. This technique enables a dynamic adaption of the physical channel: compared to solely software-based or static approaches, the LCD interference suppression filter achieves adaptive channel separation without altering the characteristics of the transmitter lights. This is especially advantageous in dual-use scenarios with illumination requirements. Additionally, external interferers, like natural light or transmitter light sources of neighboring cells in a multicell setting, can also be suppressed without requiring any control over them. Each user's LCD filter is placed in front of the corresponding photodetector and configured in such a way that only light from desired transmitters can reach the detector by setting only the appropriate pixels to transparent, while light from unwanted transmitters remains blocked. The effectiveness of this method is tested and benchmarked against zero-forcing (ZF) precoding in different scenarios and applications by numerical simulations and also verified experimentally in a large MIMO VLC testbed created specifically for this purpose

Estimation of Sparse MIMO Channels with Common Support

We consider the problem of estimating sparse communication channels in the MIMO context. In small to medium bandwidth communications, as in the current standards for OFDM and CDMA communication systems (with bandwidth up to 20 MHz), such channels are individually sparse and at the same time share a common support set. Since the underlying physical channels are inherently continuous-time, we propose a parametric sparse estimation technique based on finite rate of innovation (FRI) principles. Parametric estimation is especially relevant to MIMO communications as it allows for a robust estimation and concise description of the channels. The core of the algorithm is a generalization of conventional spectral estimation methods to multiple input signals with common support. We show the application of our technique for channel estimation in OFDM (uniformly/contiguous DFT pilots) and CDMA downlink (Walsh-Hadamard coded schemes). In the presence of additive white Gaussian noise, theoretical lower bounds on the estimation of SCS channel parameters in Rayleigh fading conditions are derived. Finally, an analytical spatial channel model is derived, and simulations on this model in the OFDM setting show the symbol error rate (SER) is reduced by a factor 2 (0 dB of SNR) to 5 (high SNR) compared to standard non-parametric methods - e.g. lowpass interpolation.Comment: 12 pages / 7 figures. Submitted to IEEE Transactions on Communicatio

Massive MIMO systems for 5G: a systematic mapping study on antenna design challenges and channel estimation open issues

The next generation of mobile networks (5G) is expected to achieve high data rates, reduce latency, as well as improve the spectral and energy efficiency of wireless communication systems. Several technologies are being explored to be used in 5G systems. One of the main promising technologies that is seen to be the enabler of 5G is massive multiple-input multiple-output (mMIMO) systems. Numerous studies have indicated the utility of mMIMO in upcoming wireless networks. However, there are several challenges that needs to be unravelled. In this paper, the latest progress of research on challenges in mMIMO systems is tracked, in the context of mutual coupling, antenna selection, pilot contamination and feedback overhead. The results of a systematic mapping study performed on 63 selected primary studies, published between the year 2017 till the second quarter of 2020, are presented. The main objective of this secondary study is to identify the challenges regarding antenna design and channel estimation, give an overview on the state-of-the-art solutions proposed in the literature, and finally, discuss emerging open research issues that need to be considered before the implementation of mMIMO systems in 5G networks

Enabling Technology and Algorithm Design for Location-Aware Communications

Location-awareness is emerging as a promising technique for future-generation wire­ less network to adaptively enhance and optimize its overall performance through location-enabled technologies such as location-assisted transceiver reconfiguration and routing. The availability of accurate location information of mobile users becomes the essential prerequisite for the design of such location-aware networks. Motivated by the low locationing accuracy of the Global Positioning System (GPS) in dense multipath environments, which is commonly used for acquiring location information in most of the existing wireless networks, wireless communication system-based po­sitioning systems have been investigated as alternatives to fill the gap of the GPS in coverage. Distance-based location techniques using time-of-arrival (TOA) mea­surements are commonly preferred by broadband wireless communications where the arrival time of the signal component of the First Arriving Path (FAP) can be con­verted to the distance between the receiver and the transmitter with known location. With at least three transmitters, the location of the receiver can be determined via trilatération method. However, identification of the FAP’s signal component in dense multipath scenarios is quite challenging due to the significantly weaker power of the FAP as compared with the Later Arriving Paths (LAPs) from scattering, reflection and refraction, and the superposition of these random arrival LAPs’ signal compo­ nents will become large interference to detect the FAP. In this thesis, a robust FAP detection scheme based on multipath interference cancellation is proposed to im­ prove the accuracy of location estimation in dense multipath environments. In the proposed algorithm, the signal components of LAPs is reconstructed based on the estimated channel and data with the assist of the communication receiver, and sub­ sequently removed from the received signal. Accurate FAP detection results are then achieved with the cross-correlation between the interference-suppressed signal and an augmented preamble which is the combination of the original preamble for com­ munications and the demodulated data sequences. Therefore, more precise distance estimation (hence location estimation) can be obtained with the proposed algorithm for further reliable network optimization strategy design. On the other hand, multiceli cooperative communication is another emerging technique to substantially improve the coverage and throughput of traditional cellular networks. Location-awareness also plays an important role in the design and imple­mentation of multiceli cooperation technique. With accurate location information of mobile users, the complexity of multiceli cooperation algorithm design can be dra­matically reduced by location-assisted applications, e.g., automatic cooperative base station (BS) determination and signal synchronization. Therefore, potential latency aroused by cooperative processing will be minimized. Furthermore, the cooperative BSs require the sharing of certain information, e.g., channel state information (CSI), user data and transmission parameters to perform coordination in their signaling strategies. The BSs need to have the capabilities to exchange available information with each other to follow up with the time-varying communication environment. As most of broadband wireless communication systems are already orthogonal frequency division multiplexing (OFDM)-based, a Multi-Layered OFDM System, which is spe­cially tailored for multiceli cooperation is investigated to provide parallel robust, efficient and flexible signaling links for BS coordination purposes. These layers are overlaid with data-carrying OFDM signals in both time and frequency domains and therefore, no dedicated radio resources are required for multiceli cooperative networks. In the final aspect of this thesis, an enhanced channel estimation through itera­ tive decision-directed method is investigated for OFDM system, which aims to provide more accurate estimation results with the aid of the demodulated OFDM data. The performance of traditional training sequence-based channel estimation is often lim­ ited by the length of the training. To achieve acceptable estimation performance, a long sequence has to be used which dramatically reduces the transmission efficiency of data communication. In this proposed method, the restriction of the training se­quence length can be removed and high channel estimation accuracy can be achieved with high transmission efficiency, and therefore it particular fits in multiceli coopera­tive networks. On the other hand, as the performance of the proposed FAP detection scheme also relies on the accuracy of channel estimation and data detection results, the proposed method can be combined with the FAP detection scheme to further optimize the accuracy of multipath interference cancellation and FAP detection