Project Course in Signal Processing and Digital Communication

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Project Course in Signal Processing and Digital
Communication
Yellow Group
MIMO Smart Antenna Communication over Radio
WELCOME TO THE PRESENTA- TION
Group Members
Deep Prakash
Amer Nezirovic Erik Bragnell Per
Kjellander Kim Thanh Tung
Dept. of Signals, Sensors Systems Royal
Institute of Technology
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Outline

• Introduction
• MIMO Systems
• Benefits

• Implementation
• Constraints
• Frame Packing
• Training sequences
• Synchronizaion
• Channel Estimation
• DSP Implementation
• DPLL
• Cycle Slip
• Weighting and Detection

• Background
• Problem
• Diversity

• MIMO schemes
• Space-time codes
• Singular-value decomp-osition theorem

• System Model

• Results

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Introduction

• What is a MIMO System?

• Introduction
• Background
• MIMO Schemes
• System Model
• Implementation
• Results

A MIMO system consists of several antenna
elements, plus signal processing at both
transmitter and receiver, the combination of
which exploits the spatial demension of the
mobile radio channel.

• Benefits
• High Data Rate
• Better Quality

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The Problem (Fading)

• Introduction
• Background
• MIMO Schemes
• System Model
• Implementation
• Results

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Diversity

• Introduction
• Background
• MIMO Schemes
• System Model
• Implementation
• Results

• Diversity

• How separate the received signals ?
• Space-time codes
• Singular-value decomposition

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Alamouti space-time coding

• The Alamouti space-time code (STBC)

• Introduction
• Background
• MIMO Schemes
• System Model
• Implementation
• Results

• Achieves diversity order 2m for any number m
  receiving antennas

• Power Control
• More power is transmitted on the best channel.
• Channel information is obatined at transmitter
  using feedback channel.

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Andersen Max. eigen value decomposition Algorithm

• Singular-value decomposition

• Introduction
• Background
• MIMO Schemes
• System Model
• Implementation
• Results

• Matrices U and V are used as weights at receiver
  and transmitter respectively.

• Reason for weighting
• To create parallel channels.

• Our implementation use the stongest channel
  corresponding to max. eigen value.

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System Model (Transmitter)

• Introduction
• Background
• MIMO Schemes
• System Model
• Implementation
• Results

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System Model (Receiver)

• Introduction
• Background
• MIMO Schemes
• System Model
• Implementation
• Results

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Implementation constraints

• Implementation
• Constraints
• Frame Packing
• Training Seq.
• Synchronization
• Channel Estimation
• DSP implementation
• DPLL
• Cycle slip
• Weighting

Required data rate is 40 kbit/s.Sampling rate
44.1 kHz Band width max 14 kHz to the radio
transmitter 16-QAM gt 4 bit/symbol 44.1
kHz sampling and 40 kbit/s gt4 samples/symbol
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Frame Packing

• Implementation
• Constraints
• Frame Packing
• Training Seq.
• Synchronization
• Channel Estimation
• DSP implementation
• DPLL
• Cycle slip
• Weighting

Guard symbols
Guard symbols
Training Sequence
Data
Known symbols
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Training Sequence

• Implementation
• Constraints
• Frame Packing
• Training Seq.
• Synchronization
• Channel Estimation
• DSP implementation
• DPLL
• Cycle slip
• Weighting

Two orthogonal sequences of length 16. One per
transmitter antenna. The training sequences are
BPSK modulated and not weighted.
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Synchronization

• Implementation
• Constraints
• Frame Packing
• Training Seq.
• Synchronization
• Channel Estimation
• DSP implementation
• DPLL
• Cycle slip
• Weighting

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Channel Estimation

• Implementation
• Constraints
• Frame Packing
• Training Seq.
• Synchronization
• Channel Estimation
• DSP implementation
• DPLL
• Cycle slip
• Weighting

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DSP Implementation

• Implementation
• Constraints
• Frame Packing
• Training Seq.
• Synchronization
• Channel Estimation
• DSP implementation
• DPLL
• Cycle slip
• Weighting

• Filtering takes most of the time
• In the transmitter up-sampling, pulse-shaping
  and up-conversion is replaced by poly phase
  filters.
• In the receiver low pass filter and matched
  filter is replaced by one combined filter

• Math functions like sine take a lot of time
• Use look up tables for cosine and sine

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DPLLEstimate the pass band center frequency

• Implementation
• Constraints
• Frame Packing
• Training Seq.
• Synchronization
• Channel Estimation
• DSP implementation
• DPLL
• Cycle slip
• Weighting

Before data transmission a sinusoid is sent and
the frequency is estimated in the receiver using
a Digital Phase Locked Loop (DPLL).
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Cycle Slip

• Implementation
• Constraints
• Frame Packing
• Training Seq.
• Syncronization
• Channel Estimation
• DSP implementation
• DPLL
• Cycle slip
• Weighting

ISI due to 4 samples/symbol and imperfections in
oscillator in the DSP.

• Solutions
• Interpolation
• Equalizer

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Problems with Weighting

• Implementation
• Constraints
• Frame Packing
• Training Seq.
• Synchronization
• Channel Estimation
• DSP implementation
• DPLL
• Cycle slip
• Weighting

Because of delay in the feedback channel we get a
rotation in the symbol space.

• Solution
• Use known symbols and estimate the phase drift

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Results

• Introduction
• Background
• MIMO Schemes
• Baseband Model
• Implementation
• Results

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Questions ?

• Introduction
• Background
• MIMO Schemes
• Baseband Model
• Implementation
• Results

Thank You