Selective Mapping technique for PAPR reduction in LTE-OFDM Systems

Table of Contents

I Introduction

1.1 Introduction to LTE

1.2 Technologies Involved

1.2.1 OFDM (Orthogonal Frequency Division Multiplexing)

1.2.2 OFDMA (Orthogonal Frequency Division Multiplexing Access)

1.2.3 MIMO (Multiple Input Multiple Output)

1.2.4 SC-FDMA (Single Carrier Frequency Division Multiple Access)

1.3 Brief History of OFDM

1.3.1 Multipath Channels

1.4 Basic Concepts

1.4.1 Frequency Division Multiplexing (FDM)

1.4.2 Time Division Multiplexing (TDM)

1.4.3 Orthogonal Frequency Division Multiplexing (OFDM)

1.5 Introduction to OFDM

1.5.1 Orthogonal Frequency Division Multiplexing (OFDM)

1.5.2 OFDM is a special case of FDM

1.6 SC-FDMA and OFDMA Tx-Rx Structure

1.7 Inter-Symbol Interference

1.8 Inter Carrier Interference

1.9 Understanding concept of Cyclic Prefix

1.10 OFDM using Inverse DFT

1.11 Advantages of OFDM

1.12 Disadvantages of OFDM

1.13 Peak to Average Power Ratio

1.14 PAPR Reduction Techniques

II Literature Review

2.1 Different methods for Peak-to-Average Power (PAPR) Reduction in Orthogonal Frequency Division Multiplexing (OFDM)

III Problem Identification

3.1 Clipping & Filtering

3.2 Coding

3.3 Interleaving

3.4 Companding

3.5 Peak Windowing

3.6 Addictive Corrective Function

3.7 Selected Mapping (SLM)

3.8 Tone Reservation

3.9 Tone Injection

3.10 Selective Scrambling (Interleaving)

IV Methodology

4.1 Objectives

4.2 Hardware& Software Required

4.2.1 Hardware Required

4.2.2 Software Required

4.3 Simulation model of OFDM System

4.3.1 Random Data Generator

4.3.2 Serial to Parallel Conversion

4.3.3 Modulation of Data

4.3.4 Inverse Fourier Transform

4.3.5 Guard Period

4.3.6 Parallel to Serial Converter

4.3.7 Channel

4.3.8 Receiver

4.4 Calculation of PAPR & CCDF of Original OFDM Signal

4.5 Complimentary Cumulative Distribution Function (CCDF)

4.6 Calculation of SNR & BNR of Original OFDM Signal

4.6.1 Additive White Gaussian Noise (AWGN) Channel

4.6.2 Signal to Noise Ratio (SNR)

4.6.3 Bit Error Rate (BER)

4.7 Criteria for Selection of PAPR Reduction Techniques

4.8 Definition of Efficient PAPR

V PAPR Reduction Techniques

5.1 Selective Mapping

5.2 Clipping - Based Active Constellation Extension Algorithm

5.2.1 Limitations of CB-ACE Algorithm

5.3 Exponential Companding Transform

5.3.1 Companding of original OFDM Signal by using Exponential Companding Transform

5.3.2 Advantages of Exponential Companding Transform

5.3.3 Limitation of Exponential Companding Transform

5.4 Adaptive Active Constellation extension Algorithm

VI Proposed Method

6.1 Selected Mapping with Riemann Matrix

6.2 Concept of Riemann matrices

VII Results and Discussion

7.1 PAPR vs CCDF of Original OFDM Signal

7.2 BER of Original OFDM Signal

7.3 PAPR vs CCDF of Original OFDM signal using Selective Mapping (SLM) Technique

7.4 CCDF plot for Clipping-based Active Constellation Extension (CB-ACE) Technique

7.5 BER plot for Clipping-based Active Constellation Extension (CB-ACE) Technique

7.6 CCDF plot for Adaptive Active Constellation Extension (Adaptive-ACE) Technique

7.7 BER plot for Adaptive Active Constellation Extension (Adaptive-ACE) Technique

7.8 CCDF plot for Exponential Companding Technique

7.9 BER plot for Exponential Companding Technique

7.10 CCDF plot for proposed technique- SLM with Riemann Matrix

7.11 BER plot for proposed technique- SLM with Riemann Matrix

VII Conclusion and Future Scope

Research Objectives and Topics

This thesis investigates the problem of high Peak-to-Average Power Ratio (PAPR) in OFDM-based wireless communication systems, specifically within the context of LTE. The primary objective is to evaluate existing PAPR reduction techniques and propose an improved Selective Mapping (SLM) method using Riemann matrices to achieve better PAPR performance without the overhead of side information transmission.

• Analysis of PAPR characteristics in OFDM and OFDMA signals.
• Evaluation of existing reduction techniques: Clipping, Coding, Interleaving, Companding, and Active Constellation Extension (ACE).
• Development of an improved SLM technique utilizing normalized Riemann matrices for phase rotation.
• Performance comparison based on PAPR, bit error rate (BER), and computational complexity.

Excerpt from the Book

Summary of Chapters

Introduction: Provides an overview of LTE, OFDM/OFDMA technologies, basic concepts like FDM and TDM, and the inherent PAPR challenge.

Literature Review: Discusses various historical and contemporary research papers and proposed methods for PAPR reduction in OFDM systems.

Problem Identification: Explains the impact of nonlinear power amplifiers on OFDM signals, highlighting the need for efficient PAPR reduction to maintain performance.

Methodology: Details the simulation model used for the OFDM system, including hardware/software requirements and evaluation criteria.

PAPR Reduction Techniques: Classifies and describes various PAPR reduction approaches, including clipping, coding, and scrambling techniques.

Proposed Method: Introduces the novel SLM technique using Riemann matrices to reduce PAPR without requiring the transmission of side information.

Results and Discussion: Presents comparative simulation results for various PAPR reduction techniques, analyzing metrics like CCDF, BER, and SNR.

Conclusion and Future Scope: Summarizes the findings and provides a comparative overview of the efficiency of the implemented techniques.

Keywords

OFDM, LTE, PAPR, Peak-to-Average Power Ratio, Selective Mapping, SLM, Riemann Matrix, BER, SNR, CCDF, Clipping, Active Constellation Extension, Companding, Wireless Communication, Signal Processing.

Frequently Asked Questions

What is the core problem addressed in this thesis?

The work focuses on the high Peak-to-Average Power Ratio (PAPR) inherent in OFDM signals, which leads to inefficient power amplifier usage, increased hardware complexity, and poor signal quality.

What are the primary PAPR reduction techniques evaluated?

The thesis evaluates techniques such as clipping and filtering, coding, interleaving, companding, and various forms of active constellation extension (ACE).

What is the ultimate goal of the proposed research?

The goal is to improve PAPR reduction performance while maintaining system efficiency, specifically by eliminating the need for side information in Selective Mapping (SLM).

Which scientific methodology is utilized?

The research employs numerical simulations using MATLAB, evaluating techniques based on performance metrics like the Complementary Cumulative Distribution Function (CCDF) and Bit Error Rate (BER).

What does the main body of the work cover?

The main body covers the analysis of PAPR causes, detailed literature reviews, simulation modeling of OFDM systems, implementation of specific reduction algorithms, and the comparative analysis of results.

How is the thesis characterized by its keywords?

The thesis is characterized by keywords related to multi-carrier modulation (OFDM), standards (LTE), performance metrics (PAPR, BER), and the proposed mathematical approach (Riemann Matrix).

What is the specific advantage of the proposed SLM method with Riemann matrices?

The proposed method achieves significant PAPR reduction without the need to send side information (SI) to the receiver, thus avoiding data rate loss and increased complexity.

How does the Riemann matrix structure aid the receiver?

The Riemann matrix possesses a specific, structured format that allows the receiver to generate it independently, eliminating the requirement to transmit phase sequence metadata.