implementation of software-based 2x2 mimo lte base …...1/15 seunghak lee school of electronics and...

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Seunghak Lee

School of Electronics and Computer Engineering, Hanyang University17 Haengdang-Dong, Seongdong-Gu, Seoul 133-791, Korea

Tel : 82-2-2299-6267, Fax : 82-2-2299-6263E-mail : invincible@dsplab.hanyang.ac.kr

http://dsplab.hanyang.ac.kr, Tel : 82-2-2299-6267 Fax : 82-2-2299-6263 All rights reserved by Prof. S. Choi

Implementation of software-based

2X2 MIMO LTE base station

system using GPU

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Contents

• Introduction of GPU– Structure of GPU

• Proposed System– 2x2 SM MIMO LTE system– Implementation of Scrambling– Implementation of Channel Estimation– Implemented System

• Performance Evaluation– Computation Time

• Conclusion

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1. Introduction of GPU

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• Graphics Processing Unit ( GPU )• Single Instruction Multiple Data( SIMD )• The GPU is massively parallel processor • Kernel

Structure of CUDA Memory

Block(1,0)

Computation grid

Block(0,1)

Block(1,1)

Block(2,1)

Block(0,0)

Block(1,0)

Block(2,0)

Thread(0,3)

Thread(1,3)

Thread(2,3)

Thread(3,3)

Thread(0,2)

Thread(1,2)

Thread(2,2)

Thread(3,2)

Thread(0,1)

Thread(1,1)

Thread(2,1)

Thread(3,1)

Thread(0,0)

Thread(1,0)

Thread(2,0)

Thread(3,0)

Kernel

SIMD processor architecture

DATA ALU

DATA ALU

DATA ALU

DATA ALU

DATA ALU

INSTRUCTION

DATA

DATA

DATA

DATA

DATA

Introduction of GPU – Structure of GPU

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2. Proposed System

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Proposed System – 2x2 SM MIMO LTE system

• Block diagram of 2x2 SM MIMO LTE Downlink system

• The parallelization of signal processing algorithms appropriately for the SIMD architecture - To use GPU and CPU resources effectively

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Proposed System – Implementation of Scrambling

2mod)()()(~ icibib

• Bit Scrambling – To avoid burst error that can happen during the procedure of data transmission

• Transmit bit :

• Scrambling bit :

31-bit long Pseudo-random sequence

• 10 threads for the 10 sub-frames such that 10 operations can be performed with a single instruction.

)(ib)(ic

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Proposed System – Implementation of Channel Estimation

Mapping of downlink reference signals

• 2D linear interpolation using 8 reference symbols existing in 2 resource blocks

• Linear interpolation is performed along the time axis using the reference signals (3rd , 9th / 6th , 12th)

• The frequency axis using the channel estimation obtained by the time-axis interpolation

• 500 parallel operations which consists of 10 CUDA Blocks along the horizontal axis and 50 CUDA Blocks along the vertical axis.

Resource Block1 Resource Block2

Time

Frequency

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Proposed System – Implemented System

2x2 SM MIMO LTE system

GPU: Modem

CPU:MediaPlayer

GPU: Modem

CPU:Streaming

Server

RFTransceiver

RFTransceiver

Terminal Computer Base-station Computer

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3. Performance Evaluation

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Performance Analysis – Computation Time

Transmitter Receiver

• Profiler provided by NVIDIA

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Performance Analysis – Computation Time

• Specifications of LTE : 1 frame = 10ms

• Enough for the real time processing.

GPU Processing time for 1 frame

GPU Processing time

Transmitter 4199.332 µs

Receiver 7617.342 µs

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5. Conclusion

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Conclusion

• GPU can be a solution because of its powerful computation capacity

• Also with the GPU, wireless communication systems can be implemented effectively for SDR.

• GPU can operate all waveform effectively.

LTE

CDMA

MobileWiMAX

GPU

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Q / Ainvincible@dsplab.hanyang.ac.kr