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Symbiotic Radio: Cognitive Backscattering Communications for Future Wireless Networks

Ying-Chang Liang, Qianqian Zhang, Erik G. Larsson, Geoffrey Ye Li

arXiv:2007.01506v1eess.SPeess.SY

TL;DR

Symbiotic radio (SR) addresses the need for spectrum- and energy-efficient wireless communication by combining cognitive radio and ambient backscattering communications. It enables mutually beneficial spectrum sharing through shared primary-system resources, joint decoding, and reconfigurable intelligent surfaces.

  • Problem

    SR targets the limitations of cognitive radio and ambient backscattering communications, including weak backscattering links, difficulty capturing desired ambient RF signals, and the need for reliable transceiver designs.

  • Method

    SR uses a secondary transmitter that varies reflection coefficients to send messages over primary-transmitter RF signals, with joint decoding and RIS assistance for link enhancement and signal capture.

  • Results

    SR provides mutually beneficial spectrum sharing, reduced secondary-transmission power consumption, and highly reliable backscattering communications while also supplying multipath diversity to the primary system.

  • Takeaways & Limitations

    SR offers a framework for enhanced spectrum, power, and cost efficiency through hybrid active and backscattering radios, with RIS-assisted and full-duplex variants as extensions.

Abstract

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The heterogenous wireless services and exponentially growing traffic call for novel spectrum- and energy-efficient wireless communication technologies. In this paper, a new technique, called symbiotic radio (SR), is proposed to exploit the benefits and address the drawbacks of cognitive radio (CR) and ambient backscattering communications(AmBC), leading to mutualism spectrum sharing and highly reliable backscattering communications. In particular, the secondary transmitter (STx) in SR transmits messages to the secondary receiver (SRx) over the RF signals originating from the primary transmitter (PTx) based on cognitive backscattering communications, thus the secondary system shares not only the radio spectrum, but also the power, and infrastructure with the primary system. In return, the secondary transmission provides beneficial multipath diversity to the primary system, therefore the two systems form mutualism spectrum sharing. More importantly, joint decoding is exploited at SRx to achieve highly reliable backscattering communications. To exploit the full potential of SR, in this paper, we address three fundamental tasks in SR: (1) enhancing the backscattering link via active load; (2) achieving highly reliable communications through joint decoding; and (3) capturing PTx's RF signals using reconfigurable intelligent surfaces. Emerging applications, design challenges and open research problems will also be discussed.

I. INTRODUCTION

Symbiotic radio (SR) combines cognitive radio and ambient backscattering to share spectrum, power, and infrastructure while enabling mutually beneficial primary and secondary transmissions. The paper presents SR fundamentals, reliability through joint decoding, link enhancement, RIS assistance, applications, and open challenges.

  • Scope of the paper: The paper also discusses RIS-assisted SR, full-duplex SR, emerging applications, design challenges, and open research problems.When the primary and secondary receivers coincide, they can decode both message types simultaneously; full-duplex primary transmitters can also decode secondary messages.
  • SR system model: SR lets the secondary transmitter send messages by varying reflection coefficients on RF signals from the primary transmitter, sharing spectrum, energy, and infrastructure.Unlike conventional cognitive radio, the secondary transmitter uses backscattering rather than a power-consuming active RF chain.
  • Mutualism and reliability: Joint decoding at the secondary receiver decodes both primary and secondary messages, avoiding interference and enabling highly reliable backscattering communications.The secondary transmission also provides multipath diversity to the primary system, creating mutual benefits.
  • Mutualism and reliability: SR targets enhanced spectrum efficiency through mutualism spectrum sharing and enhanced energy efficiency through highly reliable backscattering communications.These goals distinguish SR from conventional cognitive radio and ambient backscatter communications.
  • Design challenges and tasks: SR backscattering links suffer double fading and are weaker than direct links, motivating link enhancement and effective transceiver designs.Backscattering radios may also reflect all ambient signals within a frequency band, making it necessary to capture the intended RF signals.
  • Design challenges and tasks: The paper addresses three fundamental SR tasks: enhancing the backscattering link with active load or multiple antennas, achieving reliability through joint decoding, and capturing primary RF signals with RIS.These tasks respond to double fading, RF-signal selection, and transceiver-design challenges in SR.

III. BACKSCATTERING COMMUNICATION FOR SR

This section introduces backscattering circuits and explains how the STx reflects incident RF signals through controllable load impedance.

  • Backscattering Principles: The backscattering circuit reflects the incident signal x(t) as θ(t)x(t), where θ(t) is the reflection coefficient.The transmitted RF output originates from the PTx signal, while the STx controls the reflected signal through its circuit.
  • Backscattering Principles: Reflected electric fields comprise structural-mode and antenna-mode components, with the latter determined by antenna–load impedance mismatch.The structural-mode component is treated as part of environmental multipath.
  • Backscattering Principles: Changing the load impedance with a switcher produces a time-varying reflection coefficient for backscattering modulation.The supplied passages introduce the switching mechanism but do not provide the complete coefficient expression.

B. Backscattering Modulation

Backscattering modulation encodes secondary symbols through selectable reflection coefficients and can enhance weak links using active loads or multiple antenna elements.

  • Backscattering Modulation: Periodic load changes generate reflection coefficients representing information symbols, with the number of impedance states determining modulation order.For BPSK, two load impedance states represent symbols −1 and 1.
  • Backscattering Modulation: The reflection coefficient maps constellation points to circuit reflections using efficiency α, constrained for passive loads by 0 ≤ α ≤ 1 and |c|max normalization.The denominator |c|max accounts for the passive reflection coefficient not exceeding unity.
  • Backscattering Modulation: The corresponding load impedance is selected after the desired reflection coefficient is specified.
  • Enhancing Backscattering Link: Double fading weakens the backscattering link relative to the direct link, motivating active loads or multiple antenna elements such as RIS.These approaches are presented as ways to strengthen the backscattering signal and improve system benefits.
  • Enhancing Backscattering Link: Active loads with negative resistance can amplify the incident signal, but require an additional biasing source implemented with tunnel diodes or CMOS technology.

IV. TRANSCEIVER DESIGN FOR SR

SR receivers recover primary and secondary messages jointly over direct and backscattering components, using synchronized signal models and coherent detector designs.

  • Transceiver Design: Joint decoding at each receiver is used to recover both primary and secondary information messages.The section focuses on SRx detection, with PRx extension described as straightforward because of transmission symmetry.
  • Signal Models: Each secondary symbol period covers K primary symbol periods, with Tc = KTs; synchronization is required for K = 1 but asynchronous spectrum growth becomes negligible for large K.
  • Signal Models: The SRx model includes direct PTx-to-SRx and backscattering PTx-to-STx-to-SRx components, with h2 = αlg and Gaussian noise.
  • Signal Models: A corresponding PRx model uses direct channel f1 and backscattering channel f2 = αlq, and shares the same transmission structure.
  • Receiver Design: Jointly designed pilots enable estimation of h1 and h2, after which ML, linear, and SIC-based coherent receivers can jointly recover both signals.
  • Receiver Design: The ML detector estimates the primary and secondary symbols by searching candidate vectors for the minimum squared error.

1) ML Detector:

The ML detector reduces joint symbol recovery to a finite candidate search, while linear detection lowers complexity at the cost of performance degradation.

  • ML Detector: The ML detector searches K|Ac||As| possible symbol sets to jointly estimate the secondary symbol and conditional primary symbols.
  • ML Detector: Spatial MRC first decodes each primary sequence conditioned on candidate c(n), then selects the secondary candidate with minimum squared error.
  • ML Detector: The final primary estimate is the conditional estimate corresponding to the selected secondary-symbol estimate.
  • Linear Detectors: Linear detectors extract the joint signal vector xk(n) using MRC, ZF, or MMSE processing before recovering sk(n) and c(n).
  • Linear Detectors: Compared with ML detection, linear detection has lower complexity but degraded performance.

3) SIC-Based Detectors:

SIC-based detectors sequentially estimate and cancel primary and secondary signals, improving BER relative to linear detection at modest complexity cost. Related SR receiver studies also use semi-blind learning and spatial processing to recover secondary symbols.

  • 3) SIC-Based Detectors:: SIC sequentially estimates the primary symbol, cancels its direct-link signal, detects the secondary symbol by MRC, and re-estimates the primary symbol using MRC.This staged procedure treats the estimated secondary contribution as part of the channel during final primary-symbol detection.
  • 3) SIC-Based Detectors:: Closed-form BER expressions and numerical results cover multiple detectors over flat-fading and frequency-selective channels.
  • 3) SIC-Based Detectors:: Machine-learning semi-blind receivers recover secondary messages using constellation characteristics or clustering when only STx pilots and partial primary-transmission knowledge are available.
  • 3) SIC-Based Detectors:: A k-nearest-neighbors receiver projects out the direct-link signal using estimated DoA information, then classifies a beamformer-derived test statistic.

E. Comparison of SR with AmBC

SR addresses AmBC’s direct-link interference and non-coherent detection limitations through collaborative system design and joint decoding. Its achievable-rate analysis also describes how spreading and multipath affect primary and secondary performance.

  • E. Comparison of SR with AmBC: AmBC commonly uses non-coherent detection because the independently designed secondary system lacks primary modulation, pilot, and frame-structure information.
  • E. Comparison of SR with AmBC: Energy detection can lose substantial performance because it treats the direct-link signal as undesired interference.
  • E. Comparison of SR with AmBC: SR enables collaborative transmitter design and joint decoding of primary and secondary messages, allowing secondary transmission to enhance primary-system performance.
  • A. Achievable Rates: The primary symbol appears in both direct and backscattering links, so the backscattering path can serve as an additional decoding path.
  • A. Achievable Rates: For large K, spreading gain can enable perfect secondary decoding, whereas K = 1 makes perfect secondary-signal decoding challenging.
  • A. Achievable Rates: At high SNR, the secondary ergodic rate increases by about 3 bit/s/Hz for a 10 dB SNR increase, while large-K scaling depends on receive antennas and transmission period.

B. Single-Input-Single-Output (SISO) Primary Channel

For SISO primary channels, SR resource allocation jointly controls PTx transmit power and STx reflection efficiency under power and reflection constraints. Larger reflection efficiency is reported to improve both systems’ performance.

  • B. Single-Input-Single-Output (SISO) Primary Channel: SISO SR jointly adjusts PTx transmit power and STx reflection efficiency to satisfy primary and secondary performance requirements.
  • B. Single-Input-Single-Output (SISO) Primary Channel: Peak transmit power is constrained by the transmitter’s available peak power.
  • B. Single-Input-Single-Output (SISO) Primary Channel: Average transmit power is constrained by a long-term power budget, with expectations generally taken over channel realizations.
  • B. Single-Input-Single-Output (SISO) Primary Channel: The reflection efficiency α is adjustable in each fading block but must satisfy a reflection-efficiency constraint.
  • B. Single-Input-Single-Output (SISO) Primary Channel: Jointly optimizing transmit power and reflection efficiency maximizes weighted sum ergodic rate under long-term or short-term power constraints, with larger α improving both systems’ performance.

C. Multiple-Input-Single-Output (MISO) Primary Channel

For MISO primary channels, SR resource allocation uses spatial degrees of freedom to balance primary and secondary objectives. The formulation includes beamforming, power, and minimum-rate constraints, and can enhance the primary transmission through the secondary path.

  • C. Multiple-Input-Single-Output (MISO) Primary Channel: MISO SR exploits spatial degrees of freedom to balance the objectives of the primary and secondary systems.
  • C. Multiple-Input-Single-Output (MISO) Primary Channel: The transmit beamforming vector is constrained by the available power budget.
  • C. Multiple-Input-Single-Output (MISO) Primary Channel: The optimization can impose a minimum primary transmission-rate requirement.
  • C. Multiple-Input-Single-Output (MISO) Primary Channel: A minimum secondary transmission-rate requirement can also be imposed.
  • C. Multiple-Input-Single-Output (MISO) Primary Channel: Optimizing PTx beamforming and transmit power supports weighted-sum-rate maximization and power minimization while exploiting the secondary transmission’s additional signal path to enhance primary transmission.

D. Full-duplex STx

RIS-assisted symbiotic radio uses reconfigurable passive reflections to strengthen the backscattering link, selectively capture the intended primary signal, and support primary and secondary transmission objectives.

  • RIS-assisted SR: RIS-assisted SR uses multiple reflecting elements with adjustable reflection coefficients to capture primary RF signals and enhance the backscattering link.In this configuration, the RIS acts as the secondary transmitter and embeds messages over primary RF signals.
  • RIS-assisted SR: RIS reflection coefficients can be optimized for primary-system objectives when the STx carries no own messages, making conventional RIS a special case of RSR.
  • RIS-assisted SR: When reflection coefficients are properly chosen and time-invariant, the backscattering-link received SNR increases quadratically with the number of reflecting elements.
  • RIS-assisted SR: Passive beamforming lets RSR capture the intended PTx signal instead of backscattering all ambient signals, avoiding undesired interference at SRx.This design requires channel information to configure the reflection coefficients.
  • RIS-assisted SR: Joint active transmit beamforming at the PTx and backscattering beamforming at the RIS supports secondary-rate maximization or primary transmit-power minimization under constraints.

VII. FULL-DUPLEX SR (FDSR)

Full-duplex SR equips the PTx to transmit primary data while receiving backscatter from the STx, while SR applications target low-power connectivity across sensing scenarios.

  • VII. FULL-DUPLEX SR (FDSR): In FDSR, a full-duplex PTx transmits primary signals to the PRx and receives STx signals as the SRx.The system model distinguishes active-radio transmissions from backscattering-radio reflections.
  • VII. FULL-DUPLEX SR (FDSR): Self-interference at the full-duplex PTx can be canceled because the PTx knows its transmitted signal, enabling high-performance recovery of STx messages.
  • VII. FULL-DUPLEX SR (FDSR): A WiFi AP prototype achieved a communication rate of 5 Mbps at a range of 1 m while decoding STx backscatter during primary transmission.
  • Emerging applications: SR’s mutualism spectrum sharing and low power consumption make it suitable for massive access in 6G and beyond, including e-health and smart-home networks.
  • Emerging applications: For e-health, passive transmission, simple circuits, and reuse of cellular infrastructure support tiny, ultra-low-power monitoring devices.A user’s mobile phone can serve as the health-information collection center through cellular signals.

C. Environmental Monitoring

Environmental monitoring motivates low-cost, low-power SR networks, but practical deployment remains constrained by channel estimation, synchronization, hardware-energy trade-offs, and security requirements.

  • C. Environmental Monitoring: Environmental monitoring uses wireless sensors to track atmospheric and weather conditions, with sensor power consumption and transmission range as key design concerns.
  • IX. CHALLENGES AND OPPORTUNITIES: SR is presented as a promising solution for spectrum-, power-, and cost-efficient communications, while critical limitations and open problems remain.
  • IX. CHALLENGES AND OPPORTUNITIES: Accurate backscattering-channel models and lower-complexity estimation methods are needed because multiplicative channels introduce rank deficiency and correlation concerns.Pilot design must also support massive devices without causing pilot contamination.
  • IX. CHALLENGES AND OPPORTUNITIES: Low-complexity synchronization is required because traditional carrier-phase and timing recovery uses power-consuming oscillators, while weak backscatter must be recovered against a strong direct link.Active loads and multiple antennas can strengthen the backscattering link but consume power, leaving energy-efficient designs open.
  • IX. CHALLENGES AND OPPORTUNITIES: Security policies are needed because disrupting primary transmissions may also affect secondary transmission in SR’s symbiotic relationship.
  • Conclusion: The paper highlights enhanced spectrum efficiency through mutualism spectrum sharing and enhanced energy efficiency through highly reliable backscattering communications.
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