With the increasing data throughput requirements, the cellular network needs to move from homogeneous to heterogeneous system. In fact, the coexistence of different types of base stations with different capabilities such as femto/pico base stations as well as relays and macro base stations in random placements should improve the coverage and the spectral efficiency of the cellular networks.
However, the complexity of inter-cell interference management will grow drastically and traditional interference avoidance/mitigation approaches need to be revised.
Approaching this problem at the user equipment (UE), is of great interest since it can rely on little coordination among base stations.
The work presented in this thesis focuses on a downlink interference cancellation at the UE and shows that such an intelligent receiver can bring its promised benefit only if the base stations get involved in the interference cancellation, specifically in the channel estimation process. The limitations of this approach are evaluated and depending on the surrounding base stations two solutions are proposed and discussed.
Table of Contents
1 Introduction
1.1 Motivation and Objective
1.2 Outline and Organization of the Thesis
2 Fundamentals
2.1 Bit-Interleaved Coded Modulation
2.1.1 System and Signal Model
2.1.2 Low Complexity LLR Metrics for BICM Receivers
2.2 Interference-Aware System
2.2.1 IA Receiver: System & Signal Model
3 Structure of the Simulator
3.1 System Parameters & General Code Structure
3.2 Radio Propagation Channel
3.2.1 Simulation of AWGN-Channel model
3.2.2 Path Loss Channel Model
3.2.3 Simulation of Rayleigh Fading Channel
3.3 The Baseband Part of the Transmitter
3.3.1 Convolutional Coding and Puncturing
3.3.2 Bit-Interleaver
3.3.3 Bit-Level Scrambling
3.4 Interference Model
3.5 The Baseband Part of the Receiver
3.5.1 Pilot-based Channel Estimation
3.5.2 De-Puncturing and Soft Output Viterbi Decoding
3.5.3 Metric Computing Device
3.6 Base Stations Channel Estimation Enhancement
3.6.1 Serving Base Station: Holes
3.6.2 Interfering BS: Pilot Boosting
4 Simulation Results
5 Summary and Outlook
Objectives and Thematic Focus
The primary objective of this thesis is to evaluate downlink interference cancellation architectures for heterogeneous cellular networks, focusing on the development of an interference-aware receiver (IA-R) that utilizes base station coordination for improved channel estimation.
- Bit-interleaved coded modulation (BICM) performance in interference-limited scenarios.
- Evaluation of interference-aware (IA-R) versus interference-ignorant (II-R) receiver architectures.
- Impact of channel estimation quality on receiver performance in heterogeneous environments.
- Proposed solutions for performance enhancement via serving base station holes and pilot boosting.
- Validation of the proposed architectures through Monte Carlo simulations in a Matlab-based environment.
Excerpt from the Book
3.6.1 Serving Base Station: Holes
To assist the channel estimation process at the UE, the serving BS inserts holes in the positions of the interfering pilots, so that the quality of Hˆ 2 becomes solely a noise problem (Fig. 3.30).
This method will solve the problem of the channel estimation of the interfering signal by a positive SIR, but not the problem of Hˆ 1 by SIR < 0.
The serving BS must avoid a negative SIR at the OFDM symbols containing the pilots, likely by boosting the power of the transmitted signal at these positions.
Since the puncturing of Np data symbols reduces the average power of the OFDM symbol and in some standards such as LTE-Advanced it is important to keep a constant power over all symbols, we could increase the power of the pilots of the desired signal to update the overall OFDM symbol power.
Summary of Chapters
1 Introduction: Provides the motivation for the thesis, outlining the shift towards heterogeneous cellular networks and the need for intelligent interference cancellation at the user equipment.
2 Fundamentals: Introduces core concepts including Bit-Interleaved Coded Modulation (BICM) and the mathematical framework for interference-aware receivers.
3 Structure of the Simulator: Details the Matlab-based transceiver model, including propagation channel modeling, the interference environment, and proposed enhancements for channel estimation.
4 Simulation Results: Presents the performance analysis of the proposed IA-R architectures compared to II-R, demonstrating the necessity of base station support for effective interference cancellation.
5 Summary and Outlook: Consolidates the research findings and suggests future directions such as the integration of MIMO and turbo coding.
Keywords
Heterogeneous networks, Interference cancellation, Bit-interleaved coded modulation, LLR metrics, LTE, AWGN, Rayleigh fading, Channel estimation, Pilot boosting, Base station coordination, BER performance, Signal-to-Interference Ratio, Simulation testbed, Interference-aware receiver, Downlink transmission
Frequently Asked Questions
What is the core focus of this thesis?
The thesis focuses on improving downlink performance in heterogeneous cellular networks by implementing and evaluating interference-aware receivers that effectively manage co-channel interference.
What are the central thematic fields?
The research covers cellular network architectures, digital signal processing in receivers, channel modeling (AWGN and Rayleigh fading), and interference management techniques.
What is the primary research goal?
The goal is to determine how an intelligent receiver can best cancel inter-cell interference, specifically through collaborative channel estimation processes between base stations and the user equipment.
Which scientific method is applied?
The author utilizes a system-level simulation approach, implementing a baseband transceiver model in Matlab to conduct Monte Carlo simulations and evaluate Bit Error Rate (BER) performance.
What is covered in the main section of the work?
The main section details the construction of an LTE-compliant simulation testbed, including transmitter and receiver baseband components, interference models, and two specific optimization techniques for channel estimation: pilot holes and pilot boosting.
Which keywords characterize this work?
Key terms include heterogeneous cellular networks, interference cancellation, BICM, channel estimation, pilot boosting, and performance evaluation under various signal-to-interference ratios.
How does the "Pilot Boosting" method benefit the receiver?
Pilot boosting allows the interfering base station to adjust its power allocation, thereby reducing interference for the desired signal while maintaining overall power consistency, which improves the receiver's channel estimation quality.
Why is "Serving Base Station Holes" proposed?
This technique creates "holes" at the positions of interfering pilots to isolate the channel estimation of the interferer, reducing it to a noise-limited problem rather than an interference-limited one.
What conclusion does the author reach regarding the IA-R?
The author concludes that while the interference-aware receiver is a promising concept, it requires active support from base stations in the form of coordination or specific enhancements to function effectively in real-world scenarios.
- Citar trabajo
- Skander Kacem (Autor), 2012, Evaluation of Interference Cancellation Architectures for Heterogeneous Cellular Networks, Múnich, GRIN Verlag, https://www.grin.com/document/229965
