Modeling and Mitigation of Interference in Wireless Receivers with

74 Pages·2011·2.93 MB·English

Modeling and Mitigation of Interference in Wireless
Receivers with Multiple Antennae
Aditya Chopra

PhD Committee:
Prof. Jeffrey Andrews
Prof. Brian L. Evans (Supervisor)
Prof. Robert W. Heath, Jr.
Prof. Elmira Popova
Prof. Haris Vikalo

November 18, 2011
1
The demand for wireless Internet data is predicted to
increase 1000× over the next decade

Mobile Internet Traffic as a
Percentage of Overall Internet Traffic
Mobile Internet Data Demand (Petabytes)

12%
7
Other Mobile Internet

10% Mobile Video

8%
2x increase per year!

6% 3.5

4%

2%
0% 0
2010 2011 2012 2013 2014 2015 2010 2011 2012 2013 2014 2015

Source: Cisco Visual Networking Index Forecast

Introduction | Modeling (CoLo) | Modeling (Dist) | Outage Performance | Receiver Design 2
Wireless communication systems are increasingly using
multiple antennae to meet demand

Wireless
Channel

Transmit Antennae Receive Antennae
Benefits
Multiplexing Diversity
11

10
101110

10

Multiple data streams are transmitted Antennae with strong channels compensate for
simultaneously to increase data rate antennae with weak channels to increase reliability
Introduction | Modeling (CoLo) | Modeling (Dist) | Outage Performance | Receiver Design 3
A growing mobile user population with increasing wireless
data demand leads to interference
4
Interference is also caused by non-communicating source

Non-communicating devices
Microwave ovens Fluorescent bulbs

Computational Platform
Clocks, amplifiers, busses

Impact of platform interference Channel 7 LCD OFF
from a laptop LCD on wireless
LCD ON
throughput (IEEE 802.11g) Channel 1
[Slattery06]
0 10 20 30
Throughput (Mbps)
Introduction | Modeling (CoLo) | Modeling (Dist) | Outage Performance | Receiver Design 5
Interference mitigation has been
an active area of research over the past decade
6
I employ a statistical approach to the interference
modeling and mitigation problem

Thesis statement
Accurate statistical modeling of interference observed by multi-antenna wireless
receivers facilitates design of wireless systems with significant improvement in
communication performance in interference-limited networks.

Proposed solution
1. Model statistics of interference in multi-antenna receivers

2. Analyze performance of conventional multi-antenna receivers

3. Develop multi-antenna receiver algorithms using statistical models of
interference

Introduction | Modeling (CoLo) | Modeling (Dist) | Outage Performance | Receiver Design 7
A statistical-physical model of interference generation
and propagation

Key Features
A 3-antenna receiver within
a Poisson field of interferers
– Co-located receiver antennae ( )
2
1
– Interferers are common to all antennae ( ) 3
3
or exclusive to nth antenna ( n )
2
– Interferers are stochastically distributed in
𝛿
↓
1
space as a 2D Poisson point process
with intensity 𝜆 ( ), or 𝜆 ( n ) (per unit area)
0 𝑛 1
– Interferer free guard-zone ( ) of radius 𝛿
↑ 3
2
1
– Power law propagation and fast fading
Introduction | Modeling (CoLo) | Modeling (Dist) | Outage Performance | Receiver Design 8
Non-Gaussian distributions have been used in prior work
to model single antenna interference statistics

Guard Zone Single Antenna Characteristic Parameters Density Distribution

Radius (𝛿 ) Statistics function
↓
0 Symmetric Alpha Φ 𝜔 = 𝑒𝜎𝜔𝛼 𝜎: Dispersion, > 0 Not known except

Stable (SAS) [Sousa92] 𝛼: Index, ∈ (0,2] 𝛼=2,1,0.5
> 0 Middleton Class A Φ 𝜔 = 𝑒𝐴𝑒−𝜔22 Ω 𝐴: Impulsive index > 0 𝑓 𝑥 = ∞ 𝑚! √𝐴2𝑚𝜋Ω𝑚𝑒−𝑚𝑥2Ω
(MCA) [Middleton99] Ω: Variance > 0 𝑚=0

 Gaussian distribution
 Cauchy distribution

 Levy distribution
I derive joint statistics of interference observed by multi-
antenna receivers

1. Wireless networks with guard zones (Centralized Networks)

2. Wireless networks without guard zones (De-centralized Networks)
Introduction | Modeling (CoLo) | Modeling (Dist) | Outage Performance | Receiver Design 9
Using the system model, the sum interference at the nth
antenna is expressed as
𝛾 𝛾
− −
𝑍 = 𝐴 𝑒𝑗𝜙𝑖0𝐻 𝑒𝑗𝜃𝑖0,𝑛 𝑟 2 + 𝐴 𝑒𝑗𝜙𝑖𝑛𝐻 𝑒𝑗𝜃𝑖𝑛 𝑟 2
𝑛 𝑖 𝑖 ,𝑛 𝑖 𝑖 𝑖 𝑖
0 0 0 𝑛 𝑛 𝑛
𝑖 ∈ 𝒮 𝑖 ∈ 𝒮
0 0 𝑛 𝑛
SOURCE FADING PATHLOSS
EMISSION CHANNEL

C OMMON INTERFERERS EXCLUSIVE INTERFERERS

Multi antenna joint statistics

Single Ant.
Common interferers Independent interferers

Network model Statistics

Decentralized Symmetric Isotropic SAS [Ilow98] Independent SAS
Alpha Stable Φ 𝐰 = 𝑒𝜎0 𝐰 𝛼 𝑁
(SAS) Φ 𝐰 = 𝑒𝜎𝑛|𝜔𝑛|𝛼

𝑛=1

Centralized Middleton Independent MCA
Class A (MCA) × 𝑁 𝑤 2Ω
𝑛
−
Φ 𝐰 = 𝑒𝐴𝑛𝑒 2
𝑛=1
10
Introduction | Modeling (CoLo) | Modeling (Dist) | Outage Performance | Receiver Design