ECPRI timing measurement and testing for 5G New Radio

Abstract. Ultra low latency, increased reliability, massive network capacity, and perpetual availability are what make the 5G not just a network evolution, but a paradigm shift. Nowadays, multiple-input multiple-output, beamforming, wide bandwidth, and multi-carrier aggregation are the key enablers of the next generation of radio access technology (RAN). One of its integral part names, Base Station (BS), maintains the communication between the Network and the mobile users. The BS consists of two major elements. First, the Radio Unit transceiver module which is responsible for radio frequency processing of transmitted and received signals. Second, the Baseband unit which is charged with the digital processing of transmitted and received signals. The interface linker between these two functional blocks is called The fronthaul. To bring more agility on the Network, ORAN alliance introduces an openness concept stretched out to create an open fronthaul based on the eCPRI Protocol. Hence, the antenna data needs to be carried over longer distances introducing strict throughput latency, jitter sends, timing, and synchronization requirements. The main goal of this thesis is to guarantee the proper reception of data over the eCPRI interface, and to ensure that the RF product fulfills the ORAN requirement from a timing point of view. To achieve this target, a study process has been followed. The first phase focuses on studying the main 3 components of the environment represented by BBU 5GNR and eCPRI protocol. In the second phase, the research goes deep in the Radio module and eCPRI protocol delay management and timing, based on the ORAN specification. Finally, we define an algorithm branched out to Test Cases that can validate the 5G Radio module from Timing point of view, once they are all passed. The Test algorithm has been designed also to detect any excess in timing requirement defined by the ORAN Alliance specification. By arranging a good test plan, the algorithm has proven its high efficiency for 5GNR examination from Timing perspective

Video Transmission over MIMO-OFDM System: MDC and Space-Time Coding-Based Approaches

MIMO-OFDM is a promising technique for the broadband wireless communication system. In this paper, we propose a novel scheme that integrates multiple-description coding (MDC), error-resilient video coding, and unequal error protection strategy with hybrid space-time coding structure for robust video transmission over MIMO-OFDM system. The proposed MDC coder generates multiple bitstreams of equal importance which are very suitable for multiple-antennas system. Furthermore, according to the contribution to the reconstructed video quality, we apply unequal error protection strategy using BLAST and STBC space-time codes for each video bitstream. Experimental results have demonstrated that the proposed scheme can be an excellent alternative to achieve desired tradeoff between the reconstructed video quality and the transmission efficiency

Error resilient image transmission using T-codes and edge-embedding

Current image communication applications involve image transmission over noisy channels, where the image gets damaged. The loss of synchronization at the decoder due to these errors increases the damage in the reconstructed image. Our main goal in this research is to develop an algorithm that has the capability to detect errors, achieve synchronization and conceal errors.;In this thesis we studied the performance of T-codes in comparison with Huffman codes. We develop an algorithm for the selection of best T-code set. We have shown that T-codes exhibit better synchronization properties when compared to Huffman Codes. In this work we developed an algorithm that extracts edge patterns from each 8x8 block, classifies edge patterns into different classes. In this research we also propose a novel scrambling algorithm to hide edge pattern of a block into neighboring 8x8 blocks of the image. This scrambled hidden data is used in the detection of errors and concealment of errors. We also develop an algorithm to protect the hidden data from getting damaged in the course of transmission

A tutorial on the characterisation and modelling of low layer functional splits for flexible radio access networks in 5G and beyond

The centralization of baseband (BB) functions in a radio access network (RAN) towards data processing centres is receiving increasing interest as it enables the exploitation of resource pooling and statistical multiplexing gains among multiple cells, facilitates the introduction of collaborative techniques for different functions (e.g., interference coordination), and more efficiently handles the complex requirements of advanced features of the fifth generation (5G) new radio (NR) physical layer, such as the use of massive multiple input multiple output (MIMO). However, deciding the functional split (i.e., which BB functions are kept close to the radio units and which BB functions are centralized) embraces a trade-off between the centralization benefits and the fronthaul costs for carrying data between distributed antennas and data processing centres. Substantial research efforts have been made in standardization fora, research projects and studies to resolve this trade-off, which becomes more complicated when the choice of functional splits is dynamically achieved depending on the current conditions in the RAN. This paper presents a comprehensive tutorial on the characterisation, modelling and assessment of functional splits in a flexible RAN to establish a solid basis for the future development of algorithmic solutions of dynamic functional split optimisation in 5G and beyond systems. First, the paper explores the functional split approaches considered by different industrial fora, analysing their equivalences and differences in terminology. Second, the paper presents a harmonized analysis of the different BB functions at the physical layer and associated algorithmic solutions presented in the literature, assessing both the computational complexity and the associated performance. Based on this analysis, the paper presents a model for assessing the computational requirements and fronthaul bandwidth requirements of different functional splits. Last, the model is used to derive illustrative results that identify the major trade-offs that arise when selecting a functional split and the key elements that impact the requirements.This work has been partially funded by Huawei Technologies. Work by X. Gelabert and B. Klaiqi is partially funded by the European Union's Horizon Europe research and innovation programme (HORIZON-MSCA-2021-DN-0) under the Marie Skłodowska-Curie grant agreement No 101073265. Work by J. Perez-Romero and O. Sallent is also partially funded by the Smart Networks and Services Joint Undertaking (SNS JU) under the European Union’s Horizon Europe research and innovation programme under Grant Agreements No. 101096034 (VERGE project) and No. 101097083 (BeGREEN project) and by the Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033 under ARTIST project (ref. PID2020-115104RB-I00). This last project has also funded the work by D. Campoy.Peer ReviewedPostprint (author's final draft

Error-resilient coding tools in MPEG-4.

by Cheng Shu Ling.Thesis submitted in: July 1997.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 70-71).Abstract also in Chinese.Chapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Image Coding Standard: JPEG --- p.1Chapter 1.2 --- Video Coding Standard: MPEG --- p.6Chapter 1.2.1 --- MPEG history --- p.6Chapter 1.2.2 --- MPEG video compression algorithm overview --- p.8Chapter 1.2.3 --- More MPEG features --- p.10Chapter 1.3 --- Summary --- p.17Chapter Chapter 2 --- Error Resiliency --- p.18Chapter 2.1 --- Introduction --- p.18Chapter 2.2 --- Traditional approaches --- p.19Chapter 2.2.1 --- Channel coding --- p.19Chapter 2.2.2 --- ARQ --- p.20Chapter 2.2.3 --- Multi-layer coding --- p.20Chapter 2.2.4 --- Error Concealment --- p.20Chapter 2.3 --- MPEG-4 work on error resilience --- p.21Chapter 2.3.1 --- Resynchronization --- p.21Chapter 2.3.2 --- Data Recovery --- p.25Chapter 2.3.3 --- Error Concealment --- p.28Chapter 2.4 --- Summary --- p.29Chapter Chapter 3 --- Fixed length codes --- p.30Chapter 3.1 --- Introduction --- p.30Chapter 3.2 --- Tunstall code --- p.31Chapter 3.3 --- Lempel-Ziv code --- p.34Chapter 3.3.1 --- LZ-77 --- p.35Chapter 3.3.2 --- LZ-78 --- p.36Chapter 3.4 --- Simulation --- p.38Chapter 3.4.1 --- Experiment Setup --- p.38Chapter 3.4.2 --- Results --- p.39Chapter 3.4.3 --- Concluding Remarks --- p.42Chapter Chapter 4 --- Self-Synchronizable codes --- p.44Chapter 4.1 --- Introduction --- p.44Chapter 4.2 --- Scholtz synchronizable code --- p.45Chapter 4.2.1 --- Definition --- p.45Chapter 4.2.2 --- Construction procedure --- p.45Chapter 4.2.3 --- Synchronizer --- p.48Chapter 4.2.4 --- Effects of errors --- p.51Chapter 4.3 --- Simulation --- p.52Chapter 4.3.1 --- Experiment Setup --- p.52Chapter 4.3.2 --- Results --- p.56Chapter 4.4 --- Concluding Remarks --- p.68Chapter Chapter 5 --- Conclusions --- p.69References --- p.7

Context-based bit plane golomb coder for scalable image coding

Master'sMASTER OF ENGINEERIN