Advanced DSP Techniques for High-Capacity and Energy-Efficient Optical Fiber Communications

The rapid proliferation of the Internet has been driving communication networks closer and closer to their limits, while available bandwidth is disappearing due to an ever-increasing network load. Over the past decade, optical fiber communication technology has increased per fiber data rate from 10 Tb/s to exceeding 10 Pb/s. The major explosion came after the maturity of coherent detection and advanced digital signal processing (DSP). DSP has played a critical role in accommodating channel impairments mitigation, enabling advanced modulation formats for spectral efficiency transmission and realizing flexible bandwidth. This book aims to explore novel, advanced DSP techniques to enable multi-Tb/s/channel optical transmission to address pressing bandwidth and power-efficiency demands. It provides state-of-the-art advances and future perspectives of DSP as well

200 Gbps/lane IM/DD Technologies for Short Reach Optical Interconnects

Client-side optics are facing an ever-increasing upgrading pace, driven by upcoming 5G related services and datacenter applications. The demand for a single lane data rate is soon approaching 200 Gbps. To meet such high-speed requirement, all segments of traditional intensity modulation direct detection (IM/DD) technologies are being challenged. The characteristics of electrical and optoelectronic components and the performance of modulation, coding, and digital signal processing (DSP) techniques are being stretched to their limits. In this context, we witnessed technological breakthroughs in several aspects, including development of broadband devices, novel modulation formats and coding, and high-performance DSP algorithms for the past few years. A great momentum has been accumulated to overcome the aforementioned challenges. In this article, we focus on IM/DD transmissions, and provide an overview of recent research and development efforts on key enabling technologies for 200 Gbps per lane and beyond. Our recent demonstrations of 200 Gbps short-reach transmissions with 4-level pulse amplitude modulation (PAM) and discrete multitone signals are also presented as examples to show the system requirements in terms of device characteristics and DSP performance. Apart from digital coherent technologies and advanced direct detection systems, such as Stokes–vector and Kramers–Kronig schemes, we expect high-speed IM/DD systems will remain advantageous in terms of system cost, power consumption, and footprint for short reach applications in the short- to mid- term perspective

Towards Higher Speed Next Generation Passive Optical Networks

L'abstract è presente nell'allegato / the abstract is in the attachmen

Optics for AI and AI for Optics

Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

Millimetre-Wave Fibre-Wireless Technologies for 5G Mobile Fronthaul

The unprecedented growth in mobile data traffic, driven primarily by bandwidth rich applications and high definition video is accelerating the development of fifth generation (5G) mobile network. As mobile access network evolves towards centralisation, mobile fronthaul (MFH) architecture becomes essential in providing high capacity, ubiquitous and yet affordable services to subscribers. In order to meet the demand for high data rates in the access, Millimetre-wave (mmWave) has been highlighted as an essential technology in the development of 5G-new radio (5G-NR). In the present MFH architecture which is typically based on common public radio interface (CPRI) protocol, baseband signals are digitised before fibre transmission, featuring high overhead data and stringent synchronisation requirements. A direct application of mmWave 5G-NR to CPRI digital MFH, where signal bandwidth is expected to be up to 1GHz will be challenging, due to the increased complexity of the digitising interface and huge overhead data that will be required for such bandwidth. Alternatively, radio over fibre (RoF) technique can be employed in the transportation of mmWave wireless signals via the MFH link, thereby avoiding the expensive digitisation interface and excessive overhead associated with its implementation. Additionally, mmWave carrier can be realised with the aid of photonic components employed in the RoF link, further reducing the system complexity. However, noise and nonlinearities inherent to analog transmission presents implementation challenges, limiting the system dynamic range. Therefore, it is important to investigate the effects of these impairments in RoF based MFH architecture. This thesis presents extensive research on the impact of noise and nonlinearities on 5G candidate waveforms, in mmWave 5G fibre wireless MFH. Besides orthogonal frequency division multiplexing (OFDM), another radio access technology (RAT) that has received significant attention is filter bank multicarrier (FBMC), particularly due to its high spectral containment and excellent performance in asynchronous transmission. Hence, FBMC waveform is adopted in this work to study the impact of noise and nonlinearities on the mmWave fibre-wireless MFH architecture. Since OFDM is widely deployed and it has been adopted for 5G-NR, the performance of OFDM and FBMC based 5G mmWave RAT in fibre wireless MFH architecture is compared for several implementations and transmission scenarios. To this extent, an end to end transmission testbed is designed and implemented using industry standard VPI Transmission Maker® to investigate five mmWave upconversion techniques. Simulation results show that the impact of noise is higher in FBMC when the signal to-noise (SNR) is low, however, FBMC exhibits better performance compared to OFDM as the SNR improved. More importantly, an evaluation of the contribution of each noise component to the overall system SNR is carried out. It is observed in the investigation that noise contribution from the optical carriers employed in the heterodyne upconversion of intermediate frequency (IF) signals to mmWave frequency dominate the system noise. An adaptive modulation technique is employed to optimise the system throughput based on the received SNR. The throughput of FBMC based system reduced significantly compared to OFDM, due to laser phase noise and chromatic dispersion (CD). Additionally, it is shown that by employing frequency domain averaging technique to enhance the channel estimation (CE), the throughput of FBMC is significantly increased and consequently, a comparable performance is obtained for both waveforms. Furthermore, several coexistence scenarios for multi service transmission are studied, considering OFDM and FBMC based RATs to evaluate the impact inter band interference (IBI), due to power amplifier (PA) nonlinearity on the system performance. The low out of band (OOB) emission in FBMC plays an important role in minimising IBI to adjacent services. Therefore, FBMC requires less guardband in coexistence with multiple services in 5G fibre-wireless MFH. Conversely, OFDM introduced significant OOB to adjacent services requiring large guardband in multi-service coexistence transmission scenario. Finally, a novel transmission scheme is proposed and investigated to simultaneously generate multiple mmWave signals using laser heterodyning mmWave upconversion technique. With appropriate IF and optical frequency plan, several mmWave signals can be realised. Simulation results demonstrate successful simultaneous realisation of 28GHz, 38GHz, and 60GHz mmWave signals

Next-generation High-Capacity Communications with High Flexibility, Efficiency, and Reliability

The objective of this dissertation is to address the flexibility, efficiency and reliability in high-capacity heterogeneous communication systems. We will experimentally investigate the shaping techniques, and further extend them to more diverse and complicated scenarios, which result in more flexible systems. The scenarios include 1) entropy allocation scheme under uneven frequency response for multi-carrier system, 2) fiber-free space optics link using unipolar pairwise distribution, and 3) flexible rate passive optical network with a wide range of received optical powers. Next, we perform efficiency analysis in inter-data center and long-haul communications. We will characterize the impact of the laser linewidth, jitter tones, and the flicker noise on coherent systems with different baud rates and fiber lengths through theoretical analysis, simulation, and experimental validation. The trade-off analysis indicates the importance of setting up frequency noise power spectral density masks to qualify the transceiver laser design. Besides efficiency analysis, we will also work on efficient system architecture and algorithm design. We investigate the combined impact of various hardware impairments using proposed simplified DSP schemes in beyond 800G self-homodyne coherent system. The proposed scheme is very promising for next-generation intra-data center applications. On the other hand, to improve the data efficiency of the nonlinearity correction algorithm in broadband communication systems, we leverage the semi-supervised method and Lasso. Experimental results validate that Lasso can reduce the required pilot symbol number by exploiting the sparsity of the tap coefficients. Semi-supervised method can further enhance the system performance without introducing additional overhead. Last but not least, regarding reliability, we propose and experimentally demonstrate an ultra-reliable integrated millimeter wave and free space optics analog radio over fiber system with algorithm design. The multiple-spectra operation shows superior performance in reliability and sensitivity compared to the conventional systems, even in extreme weather conditions and strong burst interference.Ph.D

Hybrid solutions to instantaneous MIMO blind separation and decoding: narrowband, QAM and square cases

Future wireless communication systems are desired to support high data rates and high quality transmission when considering the growing multimedia applications. Increasing the channel throughput leads to the multiple input and multiple output and blind equalization techniques in recent years. Thereby blind MIMO equalization has attracted a great interest.Both system performance and computational complexities play important roles in real time communications. Reducing the computational load and providing accurate performances are the main challenges in present systems. In this thesis, a hybrid method which can provide an affordable complexity with good performance for Blind Equalization in large constellation MIMO systems is proposed first. Saving computational cost happens both in the signal sep- aration part and in signal detection part. First, based on Quadrature amplitude modulation signal characteristics, an efficient and simple nonlinear function for the Independent Compo- nent Analysis is introduced. Second, using the idea of the sphere decoding, we choose the soft information of channels in a sphere, and overcome the so- called curse of dimensionality of the Expectation Maximization (EM) algorithm and enhance the final results simultaneously. Mathematically, we demonstrate in the digital communication cases, the EM algorithm shows Newton -like convergence.Despite the widespread use of forward -error coding (FEC), most multiple input multiple output (MIMO) blind channel estimation techniques ignore its presence, and instead make the sim- plifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In final part of this work, we exploit the iterative channel estimation and decoding performance for blind MIMO equalization. Experiments show the improvements achievable by exploiting the existence of coding structures and that it can access the performance of a BCJR equalizer with perfect channel information in a reasonable SNR range. All results are confirmed experimentally for the example of blind equalization in block fading MIMO systems

Machine Learning in Digital Signal Processing for Optical Transmission Systems

The future demand for digital information will exceed the capabilities of current optical communication systems, which are approaching their limits due to component and fiber intrinsic non-linear effects. Machine learning methods are promising to find new ways of leverage the available resources and to explore new solutions. Although, some of the machine learning methods such as adaptive non-linear filtering and probabilistic modeling are not novel in the field of telecommunication, enhanced powerful architecture designs together with increasing computing power make it possible to tackle more complex problems today. The methods presented in this work apply machine learning on optical communication systems with two main contributions. First, an unsupervised learning algorithm with embedded additive white Gaussian noise (AWGN) channel and appropriate power constraint is trained end-to-end, learning a geometric constellation shape for lowest bit-error rates over amplified and unamplified links. Second, supervised machine learning methods, especially deep neural networks with and without internal cyclical connections, are investigated to combat linear and non-linear inter-symbol interference (ISI) as well as colored noise effects introduced by the components and the fiber. On high-bandwidth coherent optical transmission setups their performances and complexities are experimentally evaluated and benchmarked against conventional digital signal processing (DSP) approaches. This thesis shows how machine learning can be applied to optical communication systems. In particular, it is demonstrated that machine learning is a viable designing and DSP tool to increase the capabilities of optical communication systems

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