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Energy Efficient Source Coding and Modulation for Wireless Applications Yashwanth Prakash Sandeep.K.S.Gupta Arizona State University Tempe, AZ 85287.

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Presentation on theme: "Energy Efficient Source Coding and Modulation for Wireless Applications Yashwanth Prakash Sandeep.K.S.Gupta Arizona State University Tempe, AZ 85287."— Presentation transcript:

1 Energy Efficient Source Coding and Modulation for Wireless Applications Yashwanth Prakash Sandeep.K.S.Gupta Arizona State University Tempe, AZ 85287

2 Overview Introduction Minimum energy codes Error correction Performance comparison Conclusion

3 Introduction Wireless sensors. – Military surveillance. – Industrial monitoring. – Civilian home RF. – Medical implants (biosensors).

4 Wireless sensors Operate in the ISM band. Low data rate. Short range of operation. Demands low power and low complexity at both circuit and system level.

5 On-Off Keying Modulation Energy consumption proportional to signals transmitted. 1 0 1 0 0 1

6 Energy efficiency in OOK Reduce number of bit-1s to be transmitted. No control over the information sequence. Map source bits to codes with less number of bit-1s.

7 Minimum Energy (ME)Coding C.Erin & H.Asada (coding optimality and code book optimality). P1 P2 … Pn C1 C2 … Cn Sources with known statistics.

8 Our Approach of ME Codes Sources with unknown statistics. Minimum energy codes considered. ‘k’ Bits‘n’ Bits M Symbols = 2 k More energy efficient. - Only one bit-1 per code.

9 System Model Info SourceME codingModulator RF Transmitter 1 0 01 0 1 0 0 0 1 0 0 00 0 1 0 0 0 0 k -source bitsn - code bits ……

10 ME Code Example k = 3 n = 7 ME(n,k) = ME(7,3) 000 001 010 011 100 101 110 111 0000000 1000…0 0100…0 0010…0 …… ….. …… 0000…1 k- Bits n-Bits

11 ME codes Our approach achieves – Lesser number of bit-1 in the transmitted code – Safely assign to source symbols of any probability of occurrence. Code Rate = (k / n) = (k / 2 k -1)

12 Error Detection (Bit-by-bit hard decision) Transmitted Codeword Bits 1 0 0 0 1 0 0 …… Received Codeword bits 0.8554 0.5059 0.01 0.9229 0.2122 0.5 Threshold Detector 1 1 0 0 1 0 0 ….. Codeword in error AWGN channel

13 Performance without error correction

14 Bandwidth / Power Vs ‘n’

15 Error Correction Transmitted Codeword 01000000100000 01000000100000 0.0635 1.2360 0.0120 0.0010 0.5640 -0.021 0.640 Demodulator output Corrected Codeword AWGN Channel Select Largest instead of bit-by-bit Error Correction with soft-decision

16 Optimal Detection Transmit: Cm = [ c 1m c 2m ……… c nm ] Receive: R = [ r 1 r 2 ……… r n ] Argmax m = 1,2,… {P r (C m /R)} = MAX [ Correlation Metric] = MAX[ C(R,Cm) m = 1,2,… ] = MAX[ r 1 C 1m +r 2 C 2m +……+ r n C nm ]

17 Performance with error correction

18 Retinal Prosthesis Application at ASU BS: Base Station C: Biosensor chip C BSBS

19 Block Diagram Camera Image Processor DSP Coding/ Modulation Decode/ Demod Rx Tx Processor Power Recovery Sensor CHANNELCHANNEL

20 Thank you !!! Questions ?


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