Skip to main content
SpringerLink
Log in

Hardware-Limited Task-Based Quantization in Systems

  • Chapter
  • First Online:
Women in Telecommunications

Part of the book series: Women in Engineering and Science ((WES))

  • 154 Accesses

Abstract

In this chapter, we will consider task-oriented representation and acquisition of data in networked and distributed settings: How to acquire, represent, and encode data for the purpose of a specific task. While traditional methods and tools to represent and communicate data are task-agnostic, as they aim to reliably represent the data itself, here we consider task-based representations that directly represent the data for the purpose of a specific task. The philosophy of the approach is to leverage structure in the data itself when it exists, as with task-agnostic representations, but also to take into account the structure induced by the function or task. We will explore adapting representations to the tasks at hand to satisfy the desired constraints imposed by hardware, and by the communication network supporting the applications, considering theory, algorithms, and hardware implementations.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 99.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Agiwal M, Roy A, Saxena N (2016) Next generation 5G wireless networks: A comprehensive survey 18(3):1617–1655

    Google Scholar 

  • Alon N, Orlitsky A (1996) Source coding and graph entropies. IEEE Trans Inf Theory 42(5):1329–39

    Article  MathSciNet  MATH  Google Scholar 

  • Amer A, Hegazi E, Ragaie HF (2007) A 90-nm wideband merged CMOS LNA and mixer exploiting noise cancellation. IEEE J Solid State Circuits 42(2):323–328

    Article  Google Scholar 

  • Appuswamy R, Franceschetti M (2014) Computing linear functions by linear coding over networks. IEEE Trans Inf Theory 60(1):422–431

    Article  MathSciNet  MATH  Google Scholar 

  • Bajcsy J, Mitran P (2001) Coding for the Slepian-Wolf problem with turbo codes. In: Proc., IEEE Globecom, San Antonio, TX, vol 2, pp 1400–1404

    Google Scholar 

  • Basu S, Seo D, Varshney LR (2020) Hypergraph-based coding schemes for two source coding problems under maximal distortion. In: Proc., IEEE ISIT, Los Angeles, CA, pp 2426–2431

    Google Scholar 

  • Berger T (1978) Multiterminal source coding. The Inf Theory Approach to Commun

    Google Scholar 

  • Birkhoff G (1946) Tres observaciones sobre el algebra lineal. Univ Nac Tucuman A 5:147–154

    Google Scholar 

  • Boyd S, Vandenberghe L (2004) Convex optimization. Cambridge University Press

    Book  MATH  Google Scholar 

  • Cardinal J, Fiorini S, Van Assche G (2004) On minimum entropy graph colorings. In: Proc., IEEE ISIT, Chicago, Illinois, p 43

    Google Scholar 

  • Chen T, Chen X, Chen W, Heaton H, Liu J, Wang Z, Yin W (2021) Learning to optimize: A primer and a benchmark. Preprint. arXiv:210312828

    Google Scholar 

  • Choi J, Mo J, Heath RW (2016) Near maximum-likelihood detector and channel estimator for uplink multiuser massive MIMO systems with one-bit ADCs. IEEE Trans Commun 64(5):2005–2018

    Article  Google Scholar 

  • Choi J, Sung J, Evans BL, Gatherer A (2018) Antenna selection for large-scale MIMO systems with low-resolution ADCs. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 3594–3598

    Google Scholar 

  • Courtade TA, Wesel RD (2011) Multiterminal source coding with an entropy-based distortion measure. In: Proc., IEEE Int. Symp. Inf. Theory, Saint-Petersburg, Russia, pp 2040–2044

    Google Scholar 

  • Cover T (1975) A proof of the data compression theorem of Slepian and Wolf for ergodic sources. IEEE Trans Inf Theory 21(2):226–228

    Article  MathSciNet  MATH  Google Scholar 

  • Cover TM, Thomas JA (2012) Elements of information theory. Wiley

    MATH  Google Scholar 

  • Dattorro J (2005) Convex optimization & Euclidean distance geometry. Meboo Publishing

    MATH  Google Scholar 

  • Delgosha P, Anantharam V (2019) A notion of entropy for stochastic processes on marked rooted graphs. Preprint. arXiv:190800964

    Google Scholar 

  • Doshi V, Shah D, Médard M, Effros M (2010) Functional compression through graph coloring. IEEE Trans Inf Theory 56

    Google Scholar 

  • Eldar YC (2015) Sampling theory: beyond bandlimited systems. Cambridge Univ. Press, Cambridge, UK

    MATH  Google Scholar 

  • Ellinger F, Mayer U, Wickert M, Joram N, Wagner J, Eickhoff R, Santamaria I, Scheytt C, Kraemer R (2010) Integrated adjustable phase shifters. IEEE Microwave Mag 11(6):97–108

    Article  Google Scholar 

  • Fang J, Li H (2009) Hyperplane-based vector quantization for distributed estimation in wireless sensor networks. IEEE Trans Inf Theory 55(12):5682–5699

    Article  MathSciNet  MATH  Google Scholar 

  • Feizi S, Médard M (2014) On network functional compression. IEEE Trans Inf Theory 60(9):5387–5401

    Article  MathSciNet  MATH  Google Scholar 

  • Feng H, Effros M, Savari S (2004) Functional source coding for networks with receiver side information. In: Proc., IEEE Allerton Conf. Comm., Control and Comput., Monticello, IL, pp 1419–27

    Google Scholar 

  • Foucart S, Rauhut H (2013) A mathematical introduction to compressive sensing. Springer

    Book  MATH  Google Scholar 

  • Gács P, Körner J (1973) Common information is far less than mutual information. Probl Control Inf Theory 2(2):149–162

    MathSciNet  MATH  Google Scholar 

  • Gallager R (1988) Finding parity in a simple broadcast network. IEEE Trans Inf Theory 34(2):176–180

    Article  MathSciNet  MATH  Google Scholar 

  • Gamal AE, Kim YH (2011) Network information theory. Cambridge University Press

    Book  MATH  Google Scholar 

  • Gesbert D, Shafi M, shan Shiu D, Smith P, Naguib A (2003) From theory to practice: an overview of MIMO space-time coded wireless systems 21(3):281–302

    Google Scholar 

  • Ginsburg B, Chandrakasan A (2006) A 500MS/s 5b ADC in 65nm CMOS. In: 2006 Symposium on VLSI Circuits, 2006. Digest of Technical Papers, pp 140–141

    Google Scholar 

  • Giridhar A, Kumar P (2005) Computing and communicating functions over sensor networks. IEEE J Sel Areas Commun 23

    Google Scholar 

  • Golabighezelahmad S, Klumperink EA, Nauta B (2020) A 0.7-5.7 GHz reconfigurable MIMO receiver architecture for analog spatial notch filtering using orthogonal beamforming

    Google Scholar 

  • Gorodilova A (2019) On the differential equivalence of APN functions. Crypto Commun 11(4):793–813

    Article  MathSciNet  MATH  Google Scholar 

  • Gray RM, Stockholm TG (1993) Dithered quantizers. IEEE Trans Inf Theory 39(3):805–812

    Article  MATH  Google Scholar 

  • Heath RW, González-Prelcic N, Rangan S, Roh W, Sayeed AM (2016) An overview of signal processing techniques for millimeter wave MIMO systems. IEEE J Sel Top Signal Process 10(3):436–453

    Article  Google Scholar 

  • Ho CC, Lee TC (2012) A 10-bit 200-ms/s reconfigurable pipelined A/D converter. In: Proceedings of Technical Program of 2012 VLSI Design, Automation and Test, pp 1–4

    Google Scholar 

  • Ho T, Médard M, Koetter R, Karger D, Effros M, Shi J, Leong B (2006) A random linear network coding approach to multicast. IEEE Trans Inf Theory 52:4413–30

    Article  MathSciNet  MATH  Google Scholar 

  • Huang C, Tan Z, Yang S, Guang X (2018) Comments on cut-set bounds on network function computation. IEEE Trans Inf Theory 64(9):6454–6459

    Article  MathSciNet  MATH  Google Scholar 

  • Huang C, Hu S, Alexandropoulos GC, Zappone A, Yuen C, Zhang R, Di Renzo M, Debbah M (2020) Holographic MIMO surfaces for 6G wireless networks: Opportunities, challenges, and trends 27(5):118–125

    Google Scholar 

  • Iosif A, Ding X, Yu Y (2012) Lecture notes in optimization

    Google Scholar 

  • Ioushua SS, Eldar YC (2019) A family of hybrid analog-digital beamforming methods for massive MIMO systems 67(12):3243–3257

    MathSciNet  MATH  Google Scholar 

  • Joram N, Mayer U, Eickhoff R, Ellinger F (2009) Fully integrated active CMOS vector modulator for 802.11a compliant diversity transceivers. In: 2009 IEEE International Conference on Microwaves, Communications, Antennas and Electronics Systems, pp 1–4

    Google Scholar 

  • Kamran K, Yeh E, Ma Q (2019) DECO: Joint computation, caching and forwarding in data-centric computing networks. In: Proc., ACM MobiHoc, Catania, Italy, pp 111–120

    Google Scholar 

  • Khobahi S, Shlezinger N, Soltanalian M, Eldar YC (2021) LoRD-Net: unfolded deep detection network with low-resolution receivers. IEEE Trans Signal Process 69(11):5651–5664

    Article  MathSciNet  Google Scholar 

  • Kibaroglu K, Rebeiz GM (2017) A 0.05–6 GHz voltage-mode harmonic rejection mixer with up to 30 dBm in-band IIP3 and 35 dBc HRR in 32 nm SOI CMOS. In: 2017 IEEE Radio Frequency Integrated Circuits Symposium (RFIC), pp 304–307

    Google Scholar 

  • Kleinrock L (1975) Queuing systems vol. I: theory. Wiley, New York

    Google Scholar 

  • Koetter R, Médard M (2003) An algebraic approach to network coding. IEEE/ACM Trans Netw 11(5):782–795

    Article  Google Scholar 

  • Körner J (1973) Coding of an information source having ambiguous alphabet and the entropy of graphs. In: Proc., 6th Prague Conf. Inf. Theory, Prague, Czech Republic, pp 411–425

    Google Scholar 

  • Köse A, Médard M (2017) Scheduling wireless ad hoc networks in polynomial time using claw-free conflict graphs. In: 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), IEEE, pp 1–7

    Google Scholar 

  • Kowshik H, Kumar P (2012) Optimal function computation in directed and undirected graphs. IEEE Trans Inf Theory 58(6):3407–3418

    Article  MathSciNet  MATH  Google Scholar 

  • Krishnaswamy H, Zhang L (2016) Analog and RF interference mitigation for integrated MIMO receiver arrays 104(3):561–575

    Google Scholar 

  • Larsson EG, Edfors O, Tufvesson F, Marzetta TL (2014) Massive MIMO for next generation wireless systems 52(2):186–195

    Google Scholar 

  • Lee HS, Sodini CG (2008) Analog-to-digital converters: Digitizing the analog world. Proc IEEE 96(2):323–334

    Article  Google Scholar 

  • Leon-Garcia A (2017) Probability, statistics, and random processes for electrical engineering

    Google Scholar 

  • Li P, Shlezinger N, Zhang H, Wang B, Eldar YC (2022) Graph signal compression by joint quantization and sampling. IEEE Trans Inf Theory 70:4512–4527

    Article  MathSciNet  Google Scholar 

  • Li S, Maddah-Ali MA, Yu Q, Avestimehr AS (2018) A fundamental tradeoff between computation and communication in distributed computing. IEEE Trans Inf Theory 64:109–128

    Article  MathSciNet  MATH  Google Scholar 

  • Li SYR, Yeung RW, Cai N (2003) Linear network coding. IEEE Trans Inf Theory 49(2):371–381

    Article  MathSciNet  MATH  Google Scholar 

  • Li Y, Tao C, Seco-Granados G, Mezghani A, Swindlehurst AL, Liu L (2017a) Channel estimation and performance analysis of one-bit massive MIMO systems. IEEE Trans Signal Process 65(15):4075–4089

    Article  MathSciNet  MATH  Google Scholar 

  • Li Y, Tao C, Seco-Granados G, Mezghani A, Swindlehurst AL, Liu L (2017b) Channel estimation and performance analysis of one-bit massive MIMO systems 65(15):4075–4089

    MathSciNet  MATH  Google Scholar 

  • Ma D, Shlezinger N, Huang T, Liu Y, Eldar YC (2021) Bit constrained communication receivers in joint radar communications systems. In: Proc., IEEE ICASSP, Toronto, Canada, pp 8243–8247

    Google Scholar 

  • Malak D, Médard M (2020) Hyper binning for distributed function coding. In: Proc., IEEE Int. Workshop on Signal Process. Advances in Wireless Commun. (SPAWC)

    Google Scholar 

  • Malak D, Médard M (2023) A distributed computationally aware quantizer design via hyper binning. IEEE Trans Signal Process 71:76–91

    Article  MathSciNet  Google Scholar 

  • Max J (1960) Quantizing for minimum distortion. IRE Trans Inf Theory 6(1):7–12

    Article  MathSciNet  Google Scholar 

  • McKeown N (1999) The iSLIP scheduling algorithm for input-queued switches. IEEE/ACM Trans Netw 7(2):188–201

    Article  Google Scholar 

  • McKeown N, Mekkittikul A, Anantharam V, Walrand J (1999) Achieving 100% throughput in an input-queued switch. IEEE Trans Commun 47(8):1260–1267

    Article  Google Scholar 

  • Méndez-Rial R, Rusu C, González-Prelcic N, Alkhateeb A, Heath RW (2016) Hybrid MIMO architectures for millimeter wave communications: Phase shifters or switches? IEEE Access 4:247–267

    Article  Google Scholar 

  • Misra V, Goyal VK, Varshney LR (2011) Distributed scalar quantization for computing: High-resolution analysis and extensions. IEEE Trans Inf Theory 57(8):5298–5325

    Article  MathSciNet  MATH  Google Scholar 

  • Mo J, Alkhateeb A, Abu-Surra S, Heath RW (2017) Hybrid architectures with few-bit ADC receivers: Achievable rates and energy-rate tradeoffs 16(4):2274–2287

    Google Scholar 

  • Monga V, Li Y, Eldar YC (2021) Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing 38(2):18–44

    Google Scholar 

  • Nelson R (2013) Probability, stochastic processes, and queueing theory: the mathematics of computer performance modeling. Springer Science & Business Media

    Google Scholar 

  • Neuhaus P, Shlezinger N, Dörpinghaus M, Eldar YC, Fettweis G (2021) Task-based analog-to-digital converters. IEEE Trans Signal Process 69:5403–5418

    Article  MathSciNet  MATH  Google Scholar 

  • Ngo HQ, Larsson EG, Marzetta TL (2013) Energy and spectral efficiency of very large multiuser MIMO systems 61(4):1436–1449

    Google Scholar 

  • Orlitsky A, Roche JR (2001) Coding for computing. IEEE Trans Inf Theory 47(3):903–17

    Article  MathSciNet  MATH  Google Scholar 

  • Padmanabhan M, Bahl LR, Nahamoo D (1999) Partitioning the feature space of a classifier with linear hyperplanes. IEEE Trans Speech Audio Proc 7(3):282–288

    Article  Google Scholar 

  • Ports DRK, Nelson J (2019) When should the network be the computer? In: Proceedings of the Workshop on Hot Topics in Operating Systems, ACM, New York, NY, USA, HotOS ’19, pp 209–215

    Google Scholar 

  • Pradhan SS, Ramchandran K (2003) Distributed source coding using syndromes (DISCUS): design and construction. IEEE Trans Inf Theory 49(3):626–643

    Article  MathSciNet  MATH  Google Scholar 

  • Qian HJ, Zhang B, Luo X (2019) High-resolution wideband phase shifter with current limited vector-sum. IEEE Trans Circ Syst I Reg Papers 66(2):820–833

    Article  Google Scholar 

  • Ribeiro A, Giannakis GB (2006a) Bandwidth-constrained distributed estimation for wireless sensor networks-part I: Gaussian case. IEEE Trans Signal Proc 54(3):1131–1143

    Article  MATH  Google Scholar 

  • Ribeiro A, Giannakis GB (2006b) Bandwidth-constrained distributed estimation for wireless sensor networks-part II: unknown probability density function. IEEE Trans Signal Proc 54(7):2784–2796

    Article  MATH  Google Scholar 

  • Rini S, Chataignon J (2019) Comparison-limited vector quantization. Preprint. arXiv:190505401

    Google Scholar 

  • Rodrigues MRD, Deligiannis N, Lai L, Eldar YC (2017) Rate-distortion trade-offs in acquisition of signal parameters. In: Proc., IEEE ICASSP, New Orleans, LA, USA, pp 6105–6109

    Google Scholar 

  • Roth K, Pirzadeh H, Swindlehurst AL, Nossek JA (2018) A comparison of hybrid beamforming and digital beamforming with low-resolution ADCs for multiple users and imperfect CSI 12(3):484–498

    Google Scholar 

  • Rusek F, Persson D, Lau BK, Larsson EG, Marzetta TL, Edfors O, Tufvesson F (2013) Scaling up MIMO: Opportunities and challenges with very large arrays 30(1):40–60

    Google Scholar 

  • Salamatian S, Cohen A, Médard M (2016) Efficient coding for multi-source networks using Gács-Körner common information. In: Proc., IEEE ISITA, Monterey, CA, pp 166–170

    Google Scholar 

  • Salamatian S, Shlezinger N, Eldar YC, Médard M (2019a) Task-based quantization for recovering quadratic functions using principal inertia components. In: Proc., IEEE ISIT, Paris, France, pp 390–394

    Google Scholar 

  • Salamatian S, Shlezinger N, Eldar YC, Médard M (2019b) Task-based quantization for recovering quadratic functions using principal inertia components. In: 2019 IEEE International Symposium on Information Theory (ISIT), pp 390–394

    Google Scholar 

  • Sapio A, Canini M, Ho C, Nelson J, Kalnis P, Kim C, Krishnamurthy A, Moshref M, Ports DRK, Richtárik P (2019a) Scaling distributed machine learning with in-network aggregation. CoRR abs/1903.06701

    Google Scholar 

  • Sapio A, Canini M, Ho CY, Nelson J, Kalnis P, Kim C, Krishnamurthy A, Moshref M, Ports DR, Richtárik P (2019b) Scaling distributed machine learning with in-network aggregation. Preprint. arXiv:190306701

    Google Scholar 

  • Servetto SD (2005) Achievable rates for multiterminal source coding with scalar quantizers. In: Proc., IEEE Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, pp 1762–1766

    Google Scholar 

  • Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27(3):379–423

    Article  MathSciNet  MATH  Google Scholar 

  • Shen L, Suter BW, Tripp EE (2019) Structured sparsity promoting functions. J Optimiz Theory App 183(2):386–421

    Article  MathSciNet  MATH  Google Scholar 

  • Shlezinger N, Eldar YC (2018) On the spectral efficiency of noncooperative uplink massive MIMO systems 67(3):1956–1971

    Google Scholar 

  • Shlezinger N, Eldar YC (2020) Task-based quantization with application to MIMO receivers. Commun Inf Syst 20(2):131–162

    Article  MathSciNet  MATH  Google Scholar 

  • Shlezinger N, Eldar YC (2021) Deep task-based quantization. Entropy 23(104):1–18

    MathSciNet  Google Scholar 

  • Shlezinger N, Eldar YC, Rodrigues MR (2019a) Asymptotic task-based quantization with application to massive MIMO 67(15):3995–4012

    MathSciNet  MATH  Google Scholar 

  • Shlezinger N, Eldar YC, Rodrigues MRD (2019b) Asymptotic task-based quantization with application to massive MIMO. IEEE Trans Signal Process 67(15):3995–4012

    Article  MathSciNet  MATH  Google Scholar 

  • Shlezinger N, Eldar YC, Rodrigues MRD (2019c) Hardware-limited task-based quantization. IEEE Trans Signal Process 67(20):5223–5238

    Article  MathSciNet  MATH  Google Scholar 

  • Shlezinger N, van Sloun RJG, Huijben IAM, Tsintsadze G, Eldar YC (2020a) Learning task-based analog-to-digital conversion for MIMO receivers. In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 9125–9129

    Google Scholar 

  • Shlezinger N, Whang J, Eldar YC, Dimakis AG (2020b) Model-Based Deep Learning, to appear in Proceedings of the IEEE.

    Google Scholar 

  • Skrimponis P, Dutta S, Mezzavilla M, Rangan S, Mirfarshbafan SH, Studer C, Buckwalter J, Rodwell M (2020) Power consumption analysis for mobile MmWave and sub-THz receivers. In: 2020 2nd 6G Wireless Summit (6G SUMMIT), pp 1–5

    Google Scholar 

  • Slepian D, Wolf J (1973) Noiseless coding of correlated information sources. IEEE Trans Inf Theory 19(4):471–480

    Article  MathSciNet  MATH  Google Scholar 

  • Soer MCM, Klumperink EAM, Nauta B, van Vliet FE (2011) Spatial interferer rejection in a four-element beamforming receiver front-end with a switched-capacitor vector modulator 46(12):2933–2942

    Google Scholar 

  • Soer MCM, Klumperink EAM, van den Broek DJ, Nauta B, van Vliet FE (2017) Beamformer with constant-GM vector modulators and its spatial intermodulation distortion. IEEE J Solid State Circuits 52(3):735–746

    Article  Google Scholar 

  • Tung SY (1978) Multiterminal source coding. Cornell University

    Google Scholar 

  • Von Neumann J (1953) A certain zero-sum two-person game equivalent to the optimal assignment problem. Contrib Theory Games 2(0):5–12

    MathSciNet  Google Scholar 

  • Walden R (1999) Analog-to-digital converter survey and analysis 17(4):539–550

    Google Scholar 

  • Walrand J (1983) A probabilistic look at networks of quasi-reversible queues. IEEE Trans Info Theory 29(6):825–831

    Article  MathSciNet  MATH  Google Scholar 

  • Wang H, Shlezinger N, Eldar YC, Jin S, Imani MF, Yoo I, Smith DR (2021) Dynamic metasurface antennas for MIMO-OFDM receivers with bit-limited ADCs 69(4):2643–2659

    Google Scholar 

  • Wang J, Sahu AK, Yang Z, Joshi G, Kar S (2019) MATCHA: Speeding up decentralized SGD via matching decomposition sampling. Preprint. arXiv:190509435

    Google Scholar 

  • Wang X, Orchard MT (2001) Design of trellis codes for source coding with side information at the decoder. In: Proc., IEEE Data Compression Conference (DCC), Snowbird, UT, pp 361–370

    Google Scholar 

  • Witsenhausen H (1976) The zero-error side information problem and chromatic numbers (corresp.). IEEE Trans Inf Theory 22(5):592–593

    Article  MATH  Google Scholar 

  • Wolf J, Ziv J (1970) Transmission of noisy information to a noisy receiver with minimum distortion. IEEE Trans Inf Theory 16(4):406–411

    Article  MathSciNet  MATH  Google Scholar 

  • Xi F, Shlezinger N, Eldar YC (2021) BiLiMO: Bit-limited MIMO radar via task-based quantization. Trans Signal Process 69:6267–6282

    Article  MathSciNet  Google Scholar 

  • Yu K, Zhang YD, Bao M, Hu YH, Wang Z (2016a) DOA estimation from one-bit compressed array data via joint sparse representation. IEEE Signal Process Lett 23(9):1279–1283

    Article  Google Scholar 

  • Yu L, Li H, Chen CW (2016b) Generalized common informations: Measuring commonness by the conditional maximal correlation. Preprint. arXiv:161009289

    Google Scholar 

  • Yu Q, Maddah-Ali MA, Avestimehr AS (2018) The exact rate-memory tradeoff for caching with uncoded prefetching. IEEE Trans Inf Theory 64(2):1281–1296

    Article  MathSciNet  MATH  Google Scholar 

  • Zeitler G, Kramer G, Singer AC (2012) Bayesian parameter estimation using single-bit dithered quantization. IEEE Trans Signal Process 60(6):2713–2726

    Article  MathSciNet  MATH  Google Scholar 

  • Zirtiloglu T, Shlezinger N, Eldar YC, Yazicigil RT (2022) Power-efficient hybrid MIMO receiver with task-specific beamforming using low-resolution ADCs. In: 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). https://doi.org/10.1109/ICASSP43922.2022.9746362

Download references

Author information

Authors and Affiliations

  1. Communication Systems Department, EURECOM, Campus SophiaTech, Biot, France

    Derya Malak

  2. ECE Department, Boston University, Boston, MA, USA

    Rabia Yazicigil

  3. EECS Department, MIT, Cambridge, MA, USA

    Muriel Médard

  4. Faculty of Math & CS, Weizmann Institute of Science, Rehovot, Israel

    Xing Zhang & Yonina C. Eldar

Authors
  1. Derya Malak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rabia Yazicigil
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Muriel Médard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yonina C. Eldar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Derya Malak .

Editor information

Editors and Affiliations

  1. University of Pisa, Pisa, Pisa, Italy

    Maria Sabrina Greco

  2. University of L’Aquila, L’Aquila, Italy

    Dajana Cassioli

  3. University of Sannio, Benevento, Italy

    Silvia Liberata Ullo

  4. Freehold, NJ, USA

    Margaret J. Lyons

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Malak, D., Yazicigil, R., Médard, M., Zhang, X., Eldar, Y.C. (2023). Hardware-Limited Task-Based Quantization in Systems. In: Greco, M.S., Cassioli, D., Ullo, S.L., Lyons, M.J. (eds) Women in Telecommunications. Women in Engineering and Science. Springer, Cham. https://doi.org/10.1007/978-3-031-21975-7_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-21975-7_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21974-0

  • Online ISBN: 978-3-031-21975-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation