Thermodynamics-based Cognitive Demodulation for 'THz Torch' Wireless Communications Links

Abstract

the low-cost 'tHz torch' technology, which exploits the thermal infrared spectrum (ca. 10 to 100 THz), was recently introduced to provide secure low data rate communications links across short distances. in this paper, a thermodynamics-based approach is proposed for greatly enhancing the sensitivity of detection with non-stationary thermal radiation, generated by thermal emitters that have been modulated well beyond their thermal time constants. Here, cognitive demodulation is employed and, unlike all previous demonstrators, allows truly asynchronous operation by dynamically predicting the thermal transients for the next bit to be received. The result is a five-fold increase in the reported operational figure of merit (Range × Bit Rate) for 'THz Torch' wireless communications links. A single-channel (2 m × 125 bps) prototype and an 8-channel frequency-division multiplexed (0.5 m × 1,000 bps) prototype are demonstrated as proof-of-principle exemplars for the enhanced method of demodulation. Measurements show superior bit error rate performance with an increase in range and bit rate, when compared with conventional threshold detection. this work represents a paradigm shift in thermal-based modulation-demodulation of digital data, and offers a practical solution for the implementation of future ubiquitous secure 'THz Torch' wireless communications links; as well as other applications.Wireless links represent the fastest growing area within the digital communications industry. The history of transmitting data wirelessly can be traced back to ancient China, using smoke signaling for long-distance communication. Other early examples of wireless communications include optical telegraphy (Heliography) from the 19th century and photophone in the early 20th century 1 . Today, wireless communications systems play a crucial role in every aspects of human life.In general, wireless communications systems can be found in most parts of the electromagnetic (EM) spectrum; at radio frequencies that extend upwards into the far-infrared (i.e., covering the (sub-)microwave 2 , millimeter-wave 3 and (sub)-terahertz bands 4,5 ) and at optical wavelengths that extend downwards (i.e., across the visible light spectrum 6 into the near-infrared 7 ). However, little research and development has been reported on thermal infrared (i.e., around the near-infrared, having atmospheric transmission windows from 20-40 THz and 60-100 THz) wireless communications links. Until recently, the thermal infrared spectrum has been generally confined to applications that include motion sensing, target acquisition 8 and thermography 9 (e.g., digital thermometers and thermal cameras); having relatively low-cost components that work with incoherent radiation, when compared to extremely expensive components used in coherent systems 10 operating at radio frequencies and optical wavelengths.In 2011, the first thermal infrared wireless communications system 11 was reported, which exploited the use of extremely low-cost thermal emitters (miniature incandescent light ...

Enhanced cognitive demodulation with artificial intelligence

“…Here, the thermal-based physical layer hardware consists of a transmitter (employing miniature incandescent light bulbs or thermal emitters) and receiver (employing pyroelectric infrared (PIR) motion sensors) that supports wireless data transfer via a modulated noise carrier. The same group then went on to investigate various aspects associated with the 'THz Torch' technology, from systems level architectures down to device level enabling technologies, while trying to maintain the low-cost philosophy [2][3][4][5][6][7][8] . From this, two major scientific breakthroughs were published 7,8 : the first was in 2014, which demonstrated the secure nature of this technology 7 ; while in early 2020, the thermal time constants associated with the hardware were bypassed by introducing the new concept of 'Cognitive Demodulation' 8 .…”

“…The same group then went on to investigate various aspects associated with the 'THz Torch' technology, from systems level architectures down to device level enabling technologies, while trying to maintain the low-cost philosophy [2][3][4][5][6][7][8] . From this, two major scientific breakthroughs were published 7,8 : the first was in 2014, which demonstrated the secure nature of this technology 7 ; while in early 2020, the thermal time constants associated with the hardware were bypassed by introducing the new concept of 'Cognitive Demodulation' 8 . This powerful technique has wide-ranging implications for future communications (underwater, terrestrial and aerospace) and sensor technologies (sonar/radar/lidar and imaging), making them more resilient when operating in harsh environments.…”

“…Given two possible symbol values {S0, S1} , with ON-OFF keying (OOK) modulation, there are three predefined training sequences for timing synchronization in our 'THz Torch' wireless link: the PIR sensor calibration sequence; the thermal emitter calibration sequence, which includes four leading S1 followed by twenty S0, sent at 50 Bd; and the fixed preamble {S1, S1, S1, S0} for each data frame. The expected noiseless signal for the PIR sensor calibration sequence is essentially a step response 8 . The expected noiseless signal for the thermal emitter calibration sequence and the data frame preamble can be determined by solving Eq.…”

“…In Eq. (4) 8 , W e is switched between W R and 0, according to the training sequence. Initial conditions are T(0) = T 0 for Eq.…”

“…Naive template matching and matched filter. The basic cognitive demodulation introduced in our previous work 8 is intuitive. For synchronization, the following optimization problem is solved:…”