Microwave Real-time Analog Signal Processing (R-ASP),[1][2][3] as an alternative to DSP-based processing, might be defined as the manipulation of signals in their pristine analog form and in real time to realize specific operations enabling microwave or millimeter-wave and terahertz applications.
The surging demand for higher spectral efficiency in radio has spurred a renewed interest in analog real-time components and systems beyond conventional purely digital signal processing techniques. Although they are unrivaled at low microwave frequencies, due to their high flexibility, compact size, low cost and strong reliability, digital devices suffer of major issues, such as poor performance, high cost of A/D and D/A converters and excessive power consumption, at higher microwave and millimeter-wave frequencies. At such frequencies, analog devices and related real-time or analog signal processing (ASP) systems, which manipulate broadband signals in the time domain, may be far preferable, as they offer the benefits of lower complexity and higher speed, which may offer unprecedented solutions in the major areas of radio engineering, including communications, but also radars, sensors, instrumentation and imaging. This new technology might be seen as microwave and millimeter-wave counterpart of ultra-fast optics signal processing,[4] and has been recently enabled by a wide range of novel phasers, that are components following arbitrary group delay versus frequency responses.
The core of microwave analog signal processing is the dispersive delay structure (DDS), which differentiates frequency components of an input signal based on the group delay frequency response of the DDS. In this structure, a linear up-chirp DDS delays higher-frequency components, while a down-chirp DDS delays lower-frequency components. This frequency-selective delay characteristic makes the DDS ideal as a foundational element in microwave analog signal processing applications, such as real-time Fourier transformation. Designing DDS systems with customizable group delay responses, especially when integrated with ultra-wideband (UWB) systems, enables a broad spectrum of applications in advanced microwave signal processing.
Over the past few years, RFID systems have gained significant attention in the microwave community due to their applications in areas like communications, logistics, transportation, and security. A typical RFID system consists of a reader (interrogator) and multiple tags, which can operate over both long and short distances. RFID tags are either active or passive, with passive tags further divided into chip-based and chipless types. Chipless tags are particularly attractive due to their low cost, as they lack integrated circuits. Conventional time-domain RFIDs rely on pulse-position modulation (PPM) coding but are prone to interference from reflections. A new approach addresses this by using transmission-type all-pass dispersive delay structures (DDS/Phaser) to generate PPM codes, offering a simple, passive, and frequency-scalable RFID solution.
A dispersive delay structure (DDS) with a linear group delay response can be utilized in frequency meter applications by mapping the frequency of an incoming signal to a time delay. As the input signal travels through the DDS, each frequency component experiences a different delay, allowing the system to distinguish between frequencies based on their time delays. By increasing the slope of the group delay versus frequency (i.e., enhancing the rate of change of delay with frequency), the time delay difference between two closely spaced frequencies becomes larger. This increased time separation allows for finer resolution in distinguishing closely spaced frequencies, thus improving the frequency resolution of the meter.
A dispersive delay structure (DDS) also called Phaser with a linear group delay response can simplify frequency division multiplexing (FDM) by mapping each frequency component of the multiplexed signal to a specific time delay. In such an FDM system, a C-section all-pass DDS separates the signal's frequencies in the time domain, eliminating the need for complex analog and digital circuits typically used in conventional FDM receivers. This purely analog approach not only reduces system complexity but also avoids the limitations of digital circuits, such as high power consumption, low speed, and increased cost at high frequencies, while offering scalability across different frequency ranges.
A dispersive delay structure can play a crucial role in low-cost time-domain spectrum sniffing for cognitive radio systems. This approach leverages a group-delay phaser, which enables real-time frequency discrimination without the limitations typically associated with conventional digital spectrum sniffers that rely on fast Fourier transform (FFT) techniques. The conventional digital systems often require complex and expensive processors, particularly when handling large bandwidths and high frequencies. In contrast, the phaser-based design utilizes the passive and broadband nature of dispersive delay structures, resulting in a simple, cost-effective, and frequency-scalable architecture. By mitigating the issue of pulse spreading, which can impair frequency resolution in traditional phasers, this innovative method allows for efficient real-time spectrum analysis, identifying available frequency bands for opportunistic use, thus enhancing channel reliability and data throughput in wireless networks.
The leaky-wave antenna (LWA), as a type of dispersive structure, can be effectively utilized for real-time signal processing to create a system for incoming frequency sector detection. Its unique design allows it to radiate energy continuously along its length, making it sensitive to incoming signals from different directions and frequencies. By reconfiguring the LWA, the system can dynamically steer its detection capabilities to focus on specific angles of arrival. This enables the identification of the direction and frequency of incoming signals in real time, facilitating enhanced spectrum awareness. Coupled with a tunable bandpass filter, the LWA can isolate and analyze specific frequency bands, thereby providing valuable information about spectrum occupancy and enabling cognitive radio systems to opportunistically exploit available channels for improved efficiency and reliability in wireless communications.
Dispersive delay structures (DDS), specifically phasers with opposite chirping slopes, can significantly enhance the signal-to-noise ratio (SNR) of wideband impulse radio transceivers. In this approach, the transmitted impulse is up-chirped using an up-chirp phaser, which stretches the pulse duration while reducing its peak power, allowing for a more efficient transmission with less risk of exceeding power spectral density limits. Upon reception, the incoming signal, which contains both the desired impulse and noise, is processed through a down-chirp phaser. This phaser effectively compresses the received chirped signal back into a sharper impulse while spreading out the burst noise, which had not been pre-chirped, thus mitigating its impact. Meanwhile, Gaussian noise remains unaffected in its spectral characteristics. As a result, the desired signal is enhanced relative to the noise, achieving SNR improvements of several factors for burst and Gaussian noise types. This simple and low-cost system benefits from the broadband nature of phasers, making it suitable for applications in impulse radio ranging and communications.
Dispersion-code Multiple Access (DCMA):
Dispersion Code Multiple Access (DCMA) is an innovative patented[13] communication technique[14] that leverages Chebyshev polynomials to encode and transmit multiple data streams over a shared medium. Each data input, consisting of impulses, is encoded using a distinct Chebyshev polynomial order to create unique dispersive frequency patterns. This encoding ensures that the signals are sufficiently dispersed and distinguishable, allowing multiple users or data streams to coexist without interference. The encoded signals are then transmitted simultaneously through a common channel.
At the receiver, the system applies an inverse Chebyshev response, acting as a dispersive delay structure to decode and recover each individual data stream. This precise decoding process ensures that even weak signals, potentially buried below the noise level, can be accurately recovered, making the technique highly robust against noise and interference. DCMA offers an efficient and reliable method for multiple access communication, suitable for applications requiring strong noise immunity and optimal spectrum utilization, such as IoT networks, wireless communication, and secure data transfer.
Advantages and Challenges
Microwave real-time analog signal processing presents a transformative approach to signal processing, particularly at high frequencies where traditional digital signal processing (DSP) methods face limitations. One of the primary advantages of R-ASP is its ability to manipulate signals in their pristine analog form, allowing for lower complexity and faster processing speeds. This is crucial in applications requiring high spectral efficiency, such as communications, radar, and imaging. Additionally, R-ASP leverages dispersive delay structures, or phasers, which enhance resolution and enable real-time operations without the latency often associated with digital systems.
However, despite its benefits, R-ASP encounters several challenges that must be addressed. The enhancement of resolution, achieved through the manipulation of group delay, often leads to increased size and insertion loss in the system. These factors can compromise efficiency and signal integrity, particularly in high-bandwidth applications. Furthermore, designing and fabricating phasers with the desired higher-order group-delay responses is technically complex and costly, which may hinder the widespread implementation of R-ASP technologies.
To address these challenges, several strategies can be employed:
Advanced Material Use: Exploring novel materials, such as metamaterials or photonic crystals, can provide enhanced properties for phasers, leading to reduced size and lower insertion loss.
Optimization of Phaser Design: Implementing simulation-based design optimization tools can refine phaser characteristics, using techniques like machine learning to predict performance outcomes.
Integrated Circuit Solutions: Investigating the integration of R-ASP components with existing semiconductor technologies can create compact, high-performance integrated circuits, leveraging both analog and digital processing strengths.
Modular Design Approaches: Developing modular phaser designs that allow for easy adjustment or reconfiguration can optimize specific system requirements without necessitating entirely new designs.
Enhanced Fabrication Techniques: Utilizing advanced fabrication methods, such as 3D printing, microfabrication, or lithography, can enable the creation of complex geometries at smaller scales, reducing overall system size while maintaining performance.
Real-time Calibration and Feedback: Implementing real-time calibration techniques can dynamically adjust phaser characteristics based on operating conditions, ensuring optimal performance as environmental conditions change.
Research Collaboration: Fostering collaboration between academia, industry, and research institutions can drive innovation in phaser technology and R-ASP applications, leading to more rapid advancements in the field.
Prototype Testing and Iteration: Establishing a robust prototyping and testing framework allows for rapid iteration of designs, providing valuable insights into performance limitations and guiding future improvements.
By focusing on these strategies, researchers and engineers can work towards overcoming the current challenges in R-ASP, ultimately enhancing its viability and performance in high-frequency applications. Balancing these challenges with the inherent advantages of R-ASP will be crucial for advancing its application in next-generation wireless systems and other critical areas.
Conclusion
Microwave real-time analog signal processing emerges as a crucial innovation addressing the challenges posed by purely digital signal processing at microwave and millimeter-wave frequencies. By enabling signal manipulation in its pristine analog form and leveraging dispersive delay structures such as phasers, R-ASP provides lower complexity, faster processing speeds, and reduced power consumption—critical for high-frequency applications. With its ability to perform complex operations like pulse compression, spectrum sniffing, and real-time Fourier transformation, R-ASP is transforming fields such as communication, sensing, radar, and instrumentation.
Despite its advantages, R-ASP faces challenges, such as increased size and insertion loss associated with resolution enhancements, as well as complexities in phaser design and fabrication for higher-order responses. However, strategic approaches—such as utilizing advanced materials, optimizing phaser designs, integrating circuit solutions, and fostering research collaboration—offer pathways to overcome these limitations.
Innovations like Dispersion Code Multiple Access (DCMA) exemplify the future potential of R-ASP by combining the unique encoding capability of Chebyshev polynomials with dispersive delay-based decoding. DCMA enhances spectrum utilization by allowing multiple signals to coexist over shared media with minimal interference and excellent noise immunity, even at low signal-to-noise ratios. This seamless blend of analog signal processing principles with cutting-edge coding techniques offers transformative solutions for modern radio engineering, paving the way for high-performance communication systems and next-generation wireless applications. By continuing to address the inherent challenges of R-ASP, the field can further harness its capabilities, unlocking new opportunities and advancements in wireless technology.
Related Research Articles
Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. The digital signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space, or frequency. In digital electronics, a digital signal is represented as a pulse train, which is typically generated by the switching of a transistor.
Linear filters process time-varying input signals to produce output signals, subject to the constraint of linearity. In most cases these linear filters are also time invariant in which case they can be analyzed exactly using LTI system theory revealing their transfer functions in the frequency domain and their impulse responses in the time domain. Real-time implementations of such linear signal processing filters in the time domain are inevitably causal, an additional constraint on their transfer functions. An analog electronic circuit consisting only of linear components will necessarily fall in this category, as will comparable mechanical systems or digital signal processing systems containing only linear elements. Since linear time-invariant filters can be completely characterized by their response to sinusoids of different frequencies, they are sometimes known as frequency filters.
In electronics and telecommunications, modulation is the process of varying one or more properties of a periodic waveform, called the carrier signal, with a separate signal called the modulation signal that typically contains information to be transmitted. For example, the modulation signal might be an audio signal representing sound from a microphone, a video signal representing moving images from a video camera, or a digital signal representing a sequence of binary digits, a bitstream from a computer.
Radar is a system that uses radio waves to determine the distance (ranging), direction, and radial velocity of objects relative to the site. It is a radiodetermination method used to detect and track aircraft, ships, spacecraft, guided missiles, motor vehicles, map weather formations, and terrain.
A chirp is a signal in which the frequency increases (up-chirp) or decreases (down-chirp) with time. In some sources, the term chirp is used interchangeably with sweep signal. It is commonly applied to sonar, radar, and laser systems, and to other applications, such as in spread-spectrum communications. This signal type is biologically inspired and occurs as a phenomenon due to dispersion. It is usually compensated for by using a matched filter, which can be part of the propagation channel. Depending on the specific performance measure, however, there are better techniques both for radar and communication. Since it was used in radar and space, it has been adopted also for communication standards. For automotive radar applications, it is usually called linear frequency modulated waveform (LFMW).
A communication channel refers either to a physical transmission medium such as a wire, or to a logical connection over a multiplexed medium such as a radio channel in telecommunications and computer networking. A channel is used for information transfer of, for example, a digital bit stream, from one or several senders to one or several receivers. A channel has a certain capacity for transmitting information, often measured by its bandwidth in Hz or its data rate in bits per second.
Ultra-wideband is a radio technology that can use a very low energy level for short-range, high-bandwidth communications over a large portion of the radio spectrum. UWB has traditional applications in non-cooperative radar imaging. Most recent applications target sensor data collection, precise locating, and tracking. UWB support started to appear in high-end smartphones in 2019.
Dispersion is the phenomenon in which the phase velocity of a wave depends on its frequency. Sometimes the term chromatic dispersion is used to refer to optics specifically, as opposed to wave propagation in general. A medium having this common property may be termed a dispersive medium.
This is an index of articles relating to electronics and electricity or natural electricity and things that run on electricity and things that use or conduct electricity.
A spectrum analyzer measures the magnitude of an input signal versus frequency within the full frequency range of the instrument. The primary use is to measure the power of the spectrum of known and unknown signals. The input signal that most common spectrum analyzers measure is electrical; however, spectral compositions of other signals, such as acoustic pressure waves and optical light waves, can be considered through the use of an appropriate transducer. Spectrum analyzers for other types of signals also exist, such as optical spectrum analyzers which use direct optical techniques such as a monochromator to make measurements.
A variable frequency oscillator (VFO) in electronics is an oscillator whose frequency can be tuned over some range. It is a necessary component in any tunable radio transmitter and in receivers that work by the superheterodyne principle. The oscillator controls the frequency to which the apparatus is tuned.
Beamforming or spatial filtering is a signal processing technique used in sensor arrays for directional signal transmission or reception. This is achieved by combining elements in an antenna array in such a way that signals at particular angles experience constructive interference while others experience destructive interference. Beamforming can be used at both the transmitting and receiving ends in order to achieve spatial selectivity. The improvement compared with omnidirectional reception/transmission is known as the directivity of the array.
Digital room correction is a process in the field of acoustics where digital filters designed to ameliorate unfavorable effects of a room's acoustics are applied to the input of a sound reproduction system. Modern room correction systems produce substantial improvements in the time domain and frequency domain response of the sound reproduction system.
Pulse compression is a signal processing technique commonly used by radar, sonar and echography to either increase the range resolution when pulse length is constrained or increase the signal to noise ratio when the peak power and the bandwidth of the transmitted signal are constrained. This is achieved by modulating the transmitted pulse and then correlating the received signal with the transmitted pulse.
In digital communications, chirp spread spectrum (CSS) is a spread spectrum technique that uses wideband linear frequency modulated chirp pulses to encode information. A chirp is a sinusoidal signal whose frequency increases or decreases over time.
The time-stretch analog-to-digital converter (TS-ADC), also known as the time-stretch enhanced recorder (TiSER), is an analog-to-digital converter (ADC) system that has the capability of digitizing very high bandwidth signals that cannot be captured by conventional electronic ADCs. Alternatively, it is also known as the photonic time-stretch (PTS) digitizer, since it uses an optical frontend. It relies on the process of time-stretch, which effectively slows down the analog signal in time before it can be digitized by a standard electronic ADC.
Time stretch dispersive Fourier transform (TS-DFT), otherwise known as time-stretch transform (TST), temporal Fourier transform or photonic time-stretch (PTS) is a spectroscopy technique that uses optical dispersion instead of a grating or prism to separate the light wavelengths and analyze the optical spectrum in real-time. It employs group-velocity dispersion (GVD) to transform the spectrum of a broadband optical pulse into a time stretched temporal waveform. It is used to perform Fourier transformation on an optical signal on a single shot basis and at high frame rates for real-time analysis of fast dynamic processes. It replaces a diffraction grating and detector array with a dispersive fiber and single-pixel detector, enabling ultrafast real-time spectroscopy and imaging. Its nonuniform variant, warped-stretch transform, realized with nonlinear group delay, offers variable-rate spectral domain sampling, as well as the ability to engineer the time-bandwidth product of the signal's envelope to match that of the data acquisition systems acting as an information gearbox.
Christophe Caloz is a researcher and professor of electrical engineering and physics at KU Leuven. He graduated from the École Polytechnique Fédérale de Lausanne in Lausanne, Switzerland, where he received a Diploma of electrical engineering in telecommunications in 1995 and a Ph.D. in electromagnetics in 2000. From 2001 to 2004, he was a Postdoctoral Research Engineer at the Microwave Electronics Laboratory of University of California at Los Angeles. He was then a professor and a Canada Research Chair at the École Polytechnique de Montréal until 2019, before joining KU Leuven where he is the director of the Meta Research Group.
One way of outlining the subject of radio science is listing the topics associated with it by authoritative bodies.
The chirp pulse compression process transforms a long duration frequency-coded pulse into a narrow pulse of greatly increased amplitude. It is a technique used in radar and sonar systems because it is a method whereby a narrow pulse with high peak power can be derived from a long duration pulse with low peak power. Furthermore, the process offers good range resolution because the half-power beam width of the compressed pulse is consistent with the system bandwidth.
References
↑ Caloz, Christophe; Gupta S.; Zhang Q.; Nikfal B. (Sep–Oct 2013). "Analog Signal Processing: A Possible Alternative or Complement to Dominantly Digital Radio Schemes". IEEE Microwave Magazine. 14 (6): 87–103. doi:10.1109/MMM.2013.2269862. S2CID33284580.
↑ Abielmona, Samer; Gupta S.; Caloz C. (Nov 2009). "Compressive Receiver Using a CRLH-Based Dispersive Delay Line for Analog Signal Processing". IEEE Transactions on Microwave Theory and Techniques. 57 (11): 2617–2626. Bibcode:2009ITMTT..57.2617A. doi:10.1109/TMTT.2009.2031927. S2CID7969178.
↑ Gupta, Shulabh; Abielmona S.; Caloz C. (Dec 2009). "Microwave Analog Real-Time Spectrum Analyzer (RTSA) Based on the Spectral–Spatial Decomposition Property of Leaky-Wave Structures". IEEE Transactions on Microwave Theory and Techniques. 57 (12): 2989–2999. Bibcode:2009ITMTT..57.2989G. doi:10.1109/TMTT.2009.2034223. S2CID18462237.
↑ Teich, Bahaa E. A. Saleh; Malvin Carl; Teich, M. C. (2007). Fundamentals of photonics (2.ed.). Hoboken, [u.a.]: Wiley-Interscience. ISBN978-0471358329.{{cite book}}: CS1 maint: multiple names: authors list (link)
↑ S. Gupta, B. Nikfal and C. Caloz, "Chipless RFID System Based on Group Delay Engineered Dispersive Delay Structures," in IEEE Antennas and Wireless Propagation Letters, vol. 10, pp. 1366-1368, 2011, doi: 10.1109/LAWP.2011.2178058. keywords: {Radiofrequency identification;Delay;Dispersion;Time domain analysis;Microwave circuits;Encoding;All-pass networks;analog signal processing;dispersive delay structures (DDSs);group delay engineering;radio frequency identification (RFID)},
↑ Nikfal, Babak; Gupta S.; Caloz C. (Jun 2011). "Increased Group-Delay Slope Loop System for Enhanced-Resolution Analog Signal Processing". IEEE Transactions on Microwave Theory and Techniques. 59 (6): 1622–1628. Bibcode:2011ITMTT..59.1622N. doi:10.1109/TMTT.2011.2117436. S2CID16526587.
↑ B. Nikfal and C. Caloz, "Low-complexity and frequency-scalable analog real-time FDM receiver based on a dispersive delay structure," 2011 41st European Microwave Conference, Manchester, UK, 2011, pp. 397-400, doi: 10.23919/EuMC.2011.6101873. keywords: {Frequency division multiplexing;Receivers;Delay;Frequency modulation;Transmitters;Transceivers;Real time systems},
↑ B. Nikfal, S. Gupta and C. Caloz, "Low-Cost Analog Pulse Compression Technique Based on Mixing With an Auxiliary Pulse," in IEEE Microwave and Wireless Components Letters, vol. 22, no. 3, pp. 150-152, March 2012, doi: 10.1109/LMWC.2012.2184274. keywords: {Mixers;Baseband;Microwave theory and techniques;Radar;Delay;Bandwidth;Isolators;Dispersive delay structures (DDS);loop systems;pulse compression;pulse generation;ultra-wideband (UWB) technology},
↑ Nikfal, Babak; Badiere D.; Repeta M.; Deforge B.; Gupta S.; Caloz C. (Nov 2012). "Distortion-Less Real-Time Spectrum Sniffing Based on a Stepped Group-Delay Phaser". IEEE Microwave and Wireless Components Letters. 22 (11): 601–603. doi:10.1109/LMWC.2012.2219514. S2CID42399893.
↑ B. Nikfal and C. Caloz, "Real-time sector detection based on a reconfigurable leaky-wave antenna," 2013 7th European Conference on Antennas and Propagation (EuCAP), Gothenburg, Sweden, 2013, pp. 1788-1790. keywords: {Silicon;Antennas;Real-time systems;Distortion measurement;Leaky-wave antenna (LWA);frequency sniffing;direction of arrival detection;cognitive radio},
↑ B. Nikfal, Q. Zhang and C. Caloz, "Enhanced-SNR Impulse Radio Transceiver Based on Phasers," in IEEE Microwave and Wireless Components Letters, vol. 24, no. 11, pp. 778-780, Nov. 2014, doi: 10.1109/LMWC.2014.2348792. keywords: {Gaussian noise;Signal to noise ratio;Dispersion;Receivers;Radio transceivers;Dispersion engineering;impulse radio;phaser;radio analog signal processing;signal-to-noise ratio},
↑ WO2015179949A1,NIKFAL, Babak; Caloz, Christophe& SALEM, Mohamed Ahmed,"A method and apparatus for encoding data using instantaneous frequency dispersion",issued 2015-12-03
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