Implementing Linear Predictive Coding based on a statistical model for LTE fronthaul

Abstract

This thesis studies the application of Linear Predictive coding (LPC) in the downlink of Long Term Evolution (LTE) fronthaul, which comprises of BBU and RRH.
This can act as an additional module in the existing system. Today, the transmission of a single complex sample from the BBU to the RRH consumes 30 bits. The
research of the thesis is to analyze the application of linear prediction theory in
the LTE downlink transmission, which will work as a compression scheme and
reduce this 30 bits to lower value, at the same time fulfill the Error Vector Magnitude (EVM) requirement stated in the LTE standards made by 3rd Generation
Partnership Project (3GPP).
As 4G-LTE and the upcoming access technologies will deal with large number of data samples in the transmission, it is an advantage if those data samples
can be compressed without destroying the information content.
LPC or linear prediction coding has been proved to be a very effective
method for speech compression in audio related applications. In this thesis,
the same logic of compression is applied on digital data samples of the LTE and
the results are analyzed.
It is found that, if LPC is applied properly on the LTE, it is possible to compress data samples efficiently and transmit them from the BBU to the RRH with
fewer bits. At the RRH those compressed data samples can be processed and
the main information data can be reconstructed, with additional quantization
error and noise. This is obvious because LPC is a lossy compression method. A
statistical model is established to generate a table of linear prediction filter coefficients which will be present both at the BBU and the RRH, when compression
and decompression of data samples are performed.
Entropy is also calculated in order to analyze the achievable compression
on an actual error vector after implementing certain compression coding such
as Huffman coding. The specific coding technique is left as a scope of future
research.

Popular Abstract

Due to the growth of number of users and faster communication methods, mobile operators have to use the allocated resources more efficiently to meet the
user demands. Like any other systems, mobile communication networks go
through series of updates over time. In mobile communication system, these
updates are known as “Releases”. The transition from 3rd Generation (3G) to
4th Generation (4G) took place with Release 8 in 2008. Many new techniques
are introduced in 4G in order to use the available resources more efficiently for
improving quality of services (QoSs).
LTE (Long term evolution) or more commonly known as 4G communication
system deals with much larger amount of data traffic than any other previous
technologies. Hence it is of utmost importance that the operators make use of
the allocated bandwidth more efficiently to serve the ever increasing number of
users. It is possible for LTE to deal with this large amount of data due to the use
of OFDM modulation technique which ensures better quality of communication.
In OFDM, there exists multiple blocks of frequency bands stacked together as a
whole, which are not related to one another.
The LTE structure is different from any previous systems. In telecommunication systems, there exists a unit which handles all the data traffic to and from
the transmitter and the receiver. This module is called the base station. In LTE,
the base station is divided into two parts namely the Baseband Unit (BBU) and
the Radio Unit (RU), where almost all the data processing takes place at the BBU,
and the RU is used as both transmitter and receiver when data is exchanged to
and from a mobile device. In recent years, a new type of architecture is proposed, which is called the C-RAN (Cloud Radio Access Network). In C-RAN,
the BBU and the RU would be placed at two different locations. Multiple BBUs
can be placed together at a single place called the BBU pool, whereas the RUs
will be placed in separate places far from the BBU pool and connected via optical
fibers. In this structure, RU is known as RRH (Remote Radio Head) as they are
separated from the BBU. One main advantage of such a structure is that, only
the RRH is placed near the user locality and the BBU can be put at the network
operator’s vicinity. This also helps in reducing the operating and maintenance
cost for the operator in many ways.
Since the LTE imposes with massive amount of data traffic on the fronthaul
(almost tenfold of the actual information data after applying error correcting coding, control signals etc.), it is very important to carry out compression of
those data traffic before they are sent from the BBU to the RU. If good compression is carried out, then it becomes possible to accommodate more users, using
the available resources. Although analog signals are used to transmit a message
from the transmitter to the receiver over a medium, it is always important to
convert those analog signal to digital signal to be transmitted from one block to
the next block for processing, through the connecting link.
The main purpose of this thesis work is to apply a compression technique
which will minimize the number of bits needed to represent each of those data
samples transmitted from the BBU to the RRH. The compression technique used
in this thesis is to employ a module which will use certain number of previous
data samples values to make a prediction of the next data sample. Then this predicted data sample is compared with the actual data sample and their difference
is found. The difference between these two samples has a low magnitude, as a
result it is possible to use lower number of bits in the digital domain to represent
this value, and finally transmitted through the link to the RRH.
At the RRH, the same prediction module is used to utilize these received
samples of low magnitude, to make a prediction of the original data samples
which are intended to be sent at the first place. In order to make the prediction
module to function properly, it is very important to set up the filter values,
which are known as the prediction coefficients. These coefficients play the role
of successfully predicting data samples which are very similar to the original
data samples. These coefficients are calculated by statistical method so that they
can be used for any set of random data sample vector in the LTE.
This thesis studies the performance of applying this prediction technique in
LTE. In order to identify the efficiency of this applied compression technique,
certain parameters are calculated using various simulations, and compared with
the set of values as specified by the main researching bodies of the LTE.
It is found that, the applied compression technique works fine in LTE as
the simulation results support the validity of the scheme. It also proves that,
it is possible to introduce this compression technique as an extension to the
upcoming upgrades of the LTE, and this will facilitate accommodating more
users with the available infrastructure resources.

• author: Nakkoul, Ghassan and Kaikobad, Mohammad Shohag Hassan
• supervisor: Stefan Höst
• organization: Department of Electrical and Information Technology
• course: EITM02 20161
• year: 2016
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering
• keywords: Entropy, LTE fronthaul, RRH, BBU, C-RAN, Quantization, LTE downlink, Cyclic prefix, LPC, EVM, OFDM, Linear predicting coding, LTE
• report number: LU/LHT-EIT 2016-552
• language: English
• id: 8895453
• date added to LUP: 2016-12-06 08:21:41
• date last changed: 2016-12-06 08:21:41