Network technologies and air Interface

Introduction

The error correcting schemes,widely used in modern systems, from one hand do not always fit the quality requirements, from the other hand are not based on the last theoretical achievements.

In this project the deeper analysis of the modern error correcting schemes in mobile networks should be performed.

Research of new efficient methods for coding and processing the signals for data transmission in sensor networks.

Project stages

LDPC codes

LDPC codes can achieve the high quality of data transmission with the comparatively low coding and decoding complexity. The procedure of coding and decoding of such codes allow effective parallel implementation. It may be used to create efficient schemes of data transmission in mobile systems based on the LDPC-codes. These schemes are supposed to use multi-channel adaptive transmission. For transmission of application multimedia data (video or audio) an unequal error protection scheme can be used.

Proposed approaches:

1. multi-Layer coding based on LDPC-codes;
2. СDMA based on LDPC-codes;
3. adaptive coding based on LDPC-codes и cascade coding schemes;
4. unequal error protection.

Transport layer coding

Transport layer coding is the method for transmission of data in networks with packet commutation. It suggests adding the redundant packets obtained in the result of the coding by the error correcting code.

This method can provide the decrease in the message delays even in the network with reliable channel. In the mobile networks it can improve the probability of message delivery in a fixed time interval.

Research targets

In this area the following results are planned:

• to develop a transport layer coding scheme for enhancement transmission in mobile networks;
• to explore the possibility of the joint coding on physical, data link and transport layers.

Project team

Victor Malishev, professor
Boris Lavrenko, postgraduate student
Anastasja Lavrenko, postgraduate student
Saint-Petersburg State Electrotechnical University

Introduction

Currently, a great number of various approaches to provide error-free transmission in modern communication systems were designed. The error correction algorithms differ both in implementation complexity and in efficiency, trying their best to correct a transmission error and to increase the throughput of a data link operating in a noisy environment.

When the channel introduces predominately random bit errors, convolutional codes provide a good solution. In burst-error channels, Reed-Solomon codes are among the best codes because errors composed of many consecutive corrupted bits translate into only a few erroneous symbols.

Evaluating adaptive error correction scheme in wireless environments is challenging because repeatable experiments are difficult: urban wireless environment cannot easily be isolated and propagation conditions vary quickly. Rigid error control policies can perform very poorly, because they either introduce too much overhead in “good” environments or are not aggressive enough in “bad” environments.

This project is aimed to carry out the choice and investigation of adaptive error correction scheme for short range wireless data transmission system. It is supposed to research the efficiency of adaptive error control policies in subject to the varying propagation and channel noise, typical for urban and industrial environment.

Implementation of short range (100…1000 meters) wireless link is based on chirp spread spectrum signals in 2.4 GHz ISM band with 60…80 MHz bandwidth. The throughput of a data link is about 500 megabit per second; packet length varies from 64 to 256 byte. Computational power “on board” is strictly limited. However, off-line error correction pre- and post processing is acceptable for some applications. Preliminary experiments in urban and industrial environment shows relatively low random bit error rate and remarkable packet loss rate, demanding development of adaptive error correction scheme with interleaving.

Project stages

The choice of coding scheme and parameters is inseparably connected with adverse propagation conditions. So, the mathematical simulation of coding schemes performance on the assumption of applying of several error models is considered as initial stage of the research. The error models corresponded as varying proportion of the burst and random bit errors is of the main interest of this study. But in spite of being known the common error distribution, constructing the adequate model provided to be a quite complicated task. Thereby it is required to accumulate and review some statistics of the most typical urban noise sources in the field experiments.

The software implementation of selected algorithm supposed to be a consecutive stage. As computational power of examined system is also constrained, such realization should be inspected for computational complexity on each development step.

To make this study complete it is intended to test the system in real working conditions.

Targets

The main purpose of this project is to work out the adaptive error correction scheme for wireless data transmission system that will be robust to variations of radio wave propagation and interference in case of urban or industrial environment.

As the focus of modern telecommunication systems shifts increasingly toward wireless mobile data transfer, the systems’ capacity of operation in unstable channel conditions is constantly improved. From a system simulation point of view this presents challenges both in terms of simulator complexity and the need to develop accurate system level models for mobile data transfer to analyze systems in different protocol layers.

Usually simulations are performed for one-user point-to-point link. Overall system performance analysis requires thousands of such trajectories. It is evident that bit-true simulations for all users result in unacceptable simulation duration.

Simulator consists of three parts:

• Mobility model

This part of the simulator moves users across the service area and provides the user velocity. Mobility around the cell accounts for need to include shadowing into the model.

• Coverage estimation

The goal of this task is to provide a sufficiently accurate coverage map of the scenario under study. The accuracy of the propagation models depend on available cartography and its resolution (pixel size), 3D cartography being the most detailed one, including terrain height, terrain morphology and shapes of buildings. In simplest case, it is possible to user attenuation models such as Okamura-Hata. Better results are obtained with the use of professional coverage planning tools (e.g., Atoll) and 3D cartography to obtain a coverage map. If possible, coverage predictions should be compared with the measurements.

• Packet channel model

To construct efficient simulation models of complicated telecommunication systems, it is valuable to have error models that can be applied directly in simulating a specific protocol layer. This can be realized using packet, or block, error models, where given data protocol packets are labeled as erroneous or error-free according to suitable criteria. By nature, such models are realizable using discrete-time stochastic processes. However, determining the structure and parameters of such processes is a nontrivial task; even assuming that accurate physical layer channel models were available for a given transmission scenario, it is often infeasible to derive analytical expressions for the resulting high-protocol layer error process. Our research is concentrated on analyzing the performance and methods of evaluating the model parameters of finite-state packet error models. Specific topics in packet channel modeling are:

• Model parameterization, i.e. determining the parameters of a high-protocol layer packet error model as functions of measurable physical reception conditions such as the signal strength and vehicle speed.
• Including byte error approximation in packet error models. That is, for cases where more detailed analysis in needed, packet error model should be able to generate approximation of byte or bit level error distribution.

The general structure for system simulator is radio access network (RAN) independent. Adding more RANs to the simulator requires only creating suitable packet error models. Currently the system simulator is being constructed for DVB-H. Project participants are encouraged to add other systems (3G, WiMAX, etc.)

Simulator can be used to analyze for example

• How different RANs could be combined to provide improved performance for users having multimode terminals.
• Quality of Service (QoS) or Quality of experience (QoE) of a video streaming service for users
• Performance of a hybrid cellular and DVB-H IP IPDC system for different RRM strategies
• Initial performance analysis of candidate 4G systems.

Contacts

Team leader: Jarkko Paavola

Team supervisor: Valery Ipatov

Students involved in the project: Jussi Poikonen