Abstract

A differential pulse coding modulation with noise shaping (NS-DPCM) is proposed to achieve better error vector magnitude (EVM) performance in a digital mobile fronthaul. Compared to previous DPCM based digital mobile fronthaul, a feedback loop combined with a finite-impulse-response (FIR) filter is added to the quantizer of DPCM encoder to operate as a quantization noise shaping technique block. The noise shaping technique increases the signal-to-quantization noise ratio by reshaping the spectrum of the quantization noise. Therefore, the noise power is at a lower level in subcarriers of OFDM signal where data is modulated and at a higher level in the subcarriers where no data is modulated. Different from the noise shaping of delta-sigma modulation, the proposed scheme utilizes the existence of unused subcarriers of OFDM signal, thus does not require oversampling at the transmitter and low pass filter at the receiver. In the experiment, the proposed NS-DPCM based mobile fronthaul transmission is demonstrated in a 25-Gb/s PAM-4 intensity modulation-direct detection optical link. Compared to the existing DPCM based mobile fronthaul, significant EVM performance improvement is achieved using the same number of quantization bits.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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    [Crossref]

2017 (5)

2015 (1)

2014 (1)

1988 (1)

B. Girod, H. Almer, L. Bengtsson, B. Christensson, and P. Weiss, “A Subjective Evaluation of Noise-Shaping Quantization for Adaptive Intra-/Interframe DPCM Coding of Color Television Signals,” IEEE Trans. Commun. 36(3), 332–346 (1988).
[Crossref]

Almer, H.

B. Girod, H. Almer, L. Bengtsson, B. Christensson, and P. Weiss, “A Subjective Evaluation of Noise-Shaping Quantization for Adaptive Intra-/Interframe DPCM Coding of Color Television Signals,” IEEE Trans. Commun. 36(3), 332–346 (1988).
[Crossref]

Bengtsson, L.

B. Girod, H. Almer, L. Bengtsson, B. Christensson, and P. Weiss, “A Subjective Evaluation of Noise-Shaping Quantization for Adaptive Intra-/Interframe DPCM Coding of Color Television Signals,” IEEE Trans. Commun. 36(3), 332–346 (1988).
[Crossref]

Chang, G. K.

Chen, J.

Cheng, L.

Christensson, B.

B. Girod, H. Almer, L. Bengtsson, B. Christensson, and P. Weiss, “A Subjective Evaluation of Noise-Shaping Quantization for Adaptive Intra-/Interframe DPCM Coding of Color Television Signals,” IEEE Trans. Commun. 36(3), 332–346 (1988).
[Crossref]

Girod, B.

B. Girod, H. Almer, L. Bengtsson, B. Christensson, and P. Weiss, “A Subjective Evaluation of Noise-Shaping Quantization for Adaptive Intra-/Interframe DPCM Coding of Color Television Signals,” IEEE Trans. Commun. 36(3), 332–346 (1988).
[Crossref]

Guidotti, D.

He, H.

He, Z.

Hu, R.

Hu, W.

Jacobsen, G.

Jiang, P.

Koning, D. D.

W. Verhelst and D. D. Koning, “Noise shaping filter design for minimally audible signal requantization,” IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics,147–150 (2001).
[Crossref]

Li, H.

Li, X.

Ling, W. A.

Liu, Y.

Lu, F.

Luo, M.

Ma, X.

Ozolins, O.

Pang, X.

Pfeiffer, T.

Popov, S.

Schatz, R.

Udalcovs, A.

Verhelst, W.

W. Verhelst and D. D. Koning, “Noise shaping filter design for minimally audible signal requantization,” IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics,147–150 (2001).
[Crossref]

Wang, J.

Weiss, P.

B. Girod, H. Almer, L. Bengtsson, B. Christensson, and P. Weiss, “A Subjective Evaluation of Noise-Shaping Quantization for Adaptive Intra-/Interframe DPCM Coding of Color Television Signals,” IEEE Trans. Commun. 36(3), 332–346 (1988).
[Crossref]

Westergren, U.

Wosinska, L.

Xiao, S.

Xin, H.

Xu, M.

Yang, Q.

Ying, K.

Yu, S.

Yu, Z.

Zhang, J.

Zhang, K.

Zhang, L.

Zhang, M.

IEEE Trans. Commun. (1)

B. Girod, H. Almer, L. Bengtsson, B. Christensson, and P. Weiss, “A Subjective Evaluation of Noise-Shaping Quantization for Adaptive Intra-/Interframe DPCM Coding of Color Television Signals,” IEEE Trans. Commun. 36(3), 332–346 (1988).
[Crossref]

J. Lightwave Technol. (2)

J. Opt. Commun. Netw. (2)

Opt. Express (3)

Other (15)

C. P. R. I. Specification, V7.0, “Common Public Radio Interface (CPRI); Interface Specification,” (2015).

S. Kim, H. Chung, and S. Kim, “Experimental demonstration of CPRI data compression based on partial bit sampling for mobile front-haul link in C-RAN,” inProceedings of Optical Fiber Communication Conference (2016), paper W1H.5.
[Crossref]

L. Zhang, X. Pang, O. Ozolins, A. Udalcovs, R. Schatz, U. Westergren, G. Jacobsen, S. Popov, S. Xiao, and J. Chen, “15-Gbaud PAM4 Digital Mobile Fronthaul with Enhanced Differential Pulse Coding Modulation supporting 122 LTE-A Channels with up to 4096QAM,” inProceedings of European Conference on Optical Communications(2017), paper W.2.B.6.

NGMN, “Next Generation Mobile Networks 5G White Paper,” whitepaper v. 1.0 (2015).

A. Pizzinat, P. Chanclou, T. Diallo, and F. Saliou, “Things you should know about fronthaul,” inProceedings of European Conference on Optical Communications (2014), paper Tu.4.2.1.

X. Liu, N. Chand, F. Effenberger, L. Zhou, and H. Lin, “Demonstration of bandwidth-efficient mobile fronthaul enabling seamless aggregation of 36 E-UTRA-like wireless signals in a single 1.1-GHz wavelength channel,” inProceedings of Optical Fiber Communication Conference (2015), paper M2J.2.
[Crossref]

X. Liu, H. Zeng, N. Chand, and F. Effenberger, “Experimental demonstration of high-throughput low-latency mobile fronthaul supporting 48 20-MHz LTE signals with 59-Gb/s CPRI-equivalent rate and 2-µs processing latency,” inProceedings of European Conference on Optical Communications (2015), paper We.4.4.3.
[Crossref]

X. Liu, H. Zeng, N. Chand, and F. Effenberger, “CPRI-compatible efficient mobile fronthaul transmission via equalized TDMA achieving 256 Gb/s CPRI-equivalent data rate in a single 10-GHz-bandwidth IM-DD channel,” inProceedings of Optical Fiber Communication Conference (2016), paper M1H.3.
[Crossref]

H. Li, Q. Yang, M. Luo, R. Hu, P. Jiang, Y. Liu, X. Li, and S. Yu, “Demonstration of bandwidth efficient and low-complexity mobile fronthaul architecture via CDM-based digital channel aggregation.” inProceedings of Optical Fiber Communication Conference (2017), paper Th3A.5.
[Crossref]

J. Wang, Z. Yu, K. Ying, J. Zhang, F. Lu, M. Xu, and G. K. Chang, “Delta-sigma modulation for digital mobile fronthaul enabling carrier aggregation of 32 4G-LTE / 30 5G-FBMC signals in a single-λ 10-Gb/s IM-DD channel,” inProceedings of Optical Fiber Communication Conference (2016), paper M1H.2.
[Crossref]

J. Terada, T. Shimada, T. Shimizu, and A. Otaka, “Optical network technologies for wireless communication network,” inProceedings of European Conference on Optical Communications(2016), paper Tu.1.F.2.

W. Verhelst and D. D. Koning, “Noise shaping filter design for minimally audible signal requantization,” IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics,147–150 (2001).
[Crossref]

D. D. Koning and W. Verhelst, “On psychoacoustic noise shaping for audio requantization,” in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, 413–416 (2003).

S. M. Kay, Modern Spectral Estimation: Theory and Application (Prentice-Hall, 1988).

X. Li, S. Zhou, H. Ji, M. Luo, Q. Yang, L. Yi, R. Hu, C. Li, S. Fu, A. Alphones, W. Zhong, and C. Yu, “Transmission of 4×28-Gb/s PAM-4 over 160-km Single Mode Fiber using 10G-Class DML and Photodiode,” inProceedings of Optical Fiber Communication Conference(2016), paper W1A.5.
[Crossref]

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Figures (8)

Fig. 1
Fig. 1 (a) PAM-4 based digital MFH architecture employing proposed NS-DPCM (b) structure of the proposed NS-DPCM encoder (c) structure of FIR filter A( Z ) in direct form.
Fig. 2
Fig. 2 (a) Illustration of comparison between previous DPCM and proposed NS-DPCM. (b) The magnitude frequency responses of the introduced weighting function W( e j2πf ) and the corresponding noise shaping function | 1+A( e j2πf ) | with 1-tap and 5-tap, respectively. SCs: subcarriers. Quant.: quantization.
Fig. 3
Fig. 3 Experimental setup and function stacks for the transmission of 25-Gb/s PAM-4 based digital MFH by employing proposed NS-DPCM and previous DPCM, (a) spectrum of the baseband OFDM signal with 30.72-MHz sampling rate. (b) spectrum of the received digitized OFDM signals using NS-DPCM. (c) CCDF of PAPR for OFDM signals with various modulation formats. DSP: digital signal processing. AWG: arbitrary waveform generator. DML: direct modulate laser. SSMF: standard single-mode fiber. VOA: variable optical attenuator. PD: photo detector. OSC: oscilloscope.
Fig. 4
Fig. 4 The power spectrum of original OFDM signal, and the quantization noise power spectrum of the received digitized OFDM signals using NS-DPCM with 5-tap noise shaping FIR filter and DPCM after 20-km SSMF transmission, respectively.
Fig. 5
Fig. 5 The EVM of each data-carrying subcarrier using DPCM and NS-DPCM with 1-tap, 3-tap, 5-tap, and 7-tap noise shaping FIR filter after 20-km SSMF transmission at received optical power (ROP) of −8dBm, respectively.
Fig. 6
Fig. 6 Measured EVM versus quantization bits by employing DPCM and NS-DPCM after 20-km SSMF transmission at ROP = −8 dBm, respectively.
Fig. 7
Fig. 7 (a) BER performance as a function of received optical power pre-RS (528/514) FEC at optical back-to-back and after 20-km SSMF transmission, respectively. (b)-(c) Selected eye diagrams of received PAM-4 signals after 20-km SSMF transmission at ROP = −13dBm and −10dBm, respectively.
Fig. 8
Fig. 8 Representative constellations of recovered 5G-NR-like wireless signals by employing (a)-(c) DPCM and (d)-(f) NS-DPCM based MFH, respectively.

Tables (1)

Tables Icon

Table 1 Required QBs, supported number of AxC containers and optical bandwidth efficiency improvement compared to CPRI using NS-DPCM based 25-Gb/s PAM-4 MFH.

Equations (7)

Equations on this page are rendered with MathJax. Learn more.

A( Z )= a 1 Z 1 + a 2 Z 2 ++ a M Z M
E q ( Z )=S( Z )+ S p ( Z )+ Q f ( Z )+Q( Z ) =( S( Z )+ S p ( Z ) )+( 1+A( Z ) )Q( Z ) ,
min a 1 , a 2 ,..., a M 0 1 | 1+A( e j2πf ) | 2 W( e j2πf )df.
E a = 0 1 | k=0 M a k e j2πf | 2 W( e j2πf )df,
E a = n=0 + ( k=0 M a k v(nk) ) 2 .
Ra=r,
R=[ r( 0 ) r( 1 ) r( 1 )   r( 0 ) r( M1 ) r( M2 ) r( M1 ) r( M2 ) r( 0 ) ].

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