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Block I. Block II. Block III. Antenna. Matrix Products. Data. Multiuser Detection. Decoder. Block IV. Correlation Matrices (Per Bit). Inverse. Detected Bits. A 0 H A 1 O(K 2 N). Delay. M U X. d. Decision Feedback. Multistage Detection (Per Window). Multiple Users. R br

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slide1

Block I

Block II

Block III

Antenna

Matrix Products

Data

Multiuser Detection

Decoder

Block IV

Correlation Matrices

(Per Bit)

Inverse

Detected Bits

A0HA1

O(K2N)

Delay

M

UX

d

Decision Feedback

Multistage Detection

(Per Window)

Multiple Users

Rbr

O(KN)

+

RbbAH

= Rbr

O(K2N)

Demod

-ulator

A0HA0

O(K2N)

b

d

Channel

Estimation

MUX

MUX

Rbr

O(KN)

O(DK2Me)

Pilot

M

UX

data’

b (known)

RbbAH

= Rbr

O(K2N)

A1HA1

O(K2N)

d

Rbb

O(K2)

pilot

The Wireless Channel

AHr

O(KND)

data

Noise + MAI

Channel Estimation

Base Station

Task A

Task B

Direct Path

Reflected Paths

Multiuser Detection

Time

User 1

User 2

Block III

Block IV

Matrix Products

A0HA1

O(DK2Me)

AHr

A0HA0

A1HA1

1

1

d

data

K

K

8.Real-Time Implementation

FPGA

High Performance Processors

VLSI

DSP

5

x 10

Data Rates for Different Levels of Pipelining and Parallelism

3

2.5

(Parallel A) (Parallel+Pipe B)

(Parallel A) (Pipe B)

(Parallel A) B

2

A B

Sequential A + B

Data Rates

1.5

Data Rate Requirement = 128 Kbps

1

Joint Work with

Praful Kaul (UIUC)

Parthasarathy Ranganathan

Dr. Sarita Adve (UIUC)

0.5

DSP + FPGA

0

9

10

11

12

13

14

15

Number of Users

IMPLEMENTING CHANNEL ESTIMATION ALGORITHMS ON HARDWARESridhar Rajagopal, Suman Das and Joseph R. Cavallaro

1.Multiuser Channel Estimation

3 .Base-station Receiver

5.Task Decomposition

Channel Effects

  • Multiple Users
    • Multiple Access Interference
  • Multipath Delays
  • Fading
  • Additive White Gaussian Noise

Parameters

  • N - Spreading Code Length
  • K - Number of Users
  • A - [A0 A1] - Channel Estimate
  • D - Multiuser Detection Window
  • r - Received bits ofKusers
    • Can beDataor Pilot(with interference/fading)
  • b - KnownPilotbits at the receiver
  • d - DetectedDatabits
  • Data’ - Datasynchronized with d
  • Multiuser Channel Estimation Methods
    • Subspace
    • Maximum Likelihood
  • Joint Estimation and Detection
    • Computationally Efficient
    • Better BER Performance

6. Exploiting Pipelining and Parallelism

4. DSP Implementation

  • Multiuser Channel Estimation
    • Need to know the Channel for proper detection
    • Delays and Amplitudes of each user and each path
  • Send sequence of known bits (Pilot / Preamble)
    • Pilot Code-Multiplexed with Data
    • Pilot Time-Multiplexed with Data
  • Multiuser Detection
    • Use knowledge of channel for reliable detection
  • TI TMSC6701, projected at 250 MHz.
  • 1953 cycles available for detection of 1 bit assuming data rate of 128 Kbps.
  • In-depth profiling to find bottlenecks.
  • Multiuser Detection
    • needs to performed continuously to meet data rate requirements
  • Channel Estimation
    • can be updated less frequently
  • Single DSP does not meet real-time requirements
  • Multiuser Detection - Bottleneck!

Task B

Task A

2.Third Generation Communication Systems

Accelerating the blocks in Multistage Detection

to meet real-time requirements.

  • W-CDMA - Wideband CDMA (5 MHz)
  • 3G Communication Systems
    • Integrating Multimedia Capabilities
    • Quality of Service (QoS)
    • Multi-rate Services
    • Higher Data Rates
      • 2048,384,144 Kbps

7. Meeting Real-Time Requirements

Graph shows the data rates achieved by different levels

of acceleration for multiuser detection.