AI-Managed Cognitive Radio Digitizers

Abstract

Embedding Artificial Intelligence (AI) in integrated circuits is one of the technology pillars of the so-called digital transformation. Nowadays, the vast majority of electronic devices benefits from digital signal processing to implement more and more functionalities, which can be further enhanced by the action of AI algorithms and artefacts. Moreover, as the analog/digital interfaces are moving closer and closer to the point where the information is either acquired or transmitted, the so-called AImanaged data converters are becoming key building blocks in an increasingly number of interconnected cyberphysical systems -made up of both software and hardware components. Software Defined Radio (SDR) and Cognitive Radio (CR) systems intended for 5G/6G communications are good examples which can benefit from an early digitization managed by AI engines.In this context, this paper presents an overview of circuits and systems techniques for AI-managed analog/digital interfaces with application in SDR/CR mobile telecom systems. Some design trends and challenges are discussed, going from new communications and computing paradigms for AIoT devices and networks, to digital-based/scaling-friendly analog circuit techniques for an efficient digitization. The state of the art on Analogto-Digital Converters (ADCs) is surveyed, putting emphasis on highly-programmable Sigma-Delta Modulators (Σ∆Ms) as one of the best ADC candidates for SDR/CR transceivers. Some chip examples are shown to illustrate their potential application in AI-enhanced CR end-devices.

Multi‐objective spectrum assignment in heterogeneous cognitive radio networks for internet of things

“…In Equation (7), p RF gives the energy consumed by the radio frequency circuit. Next, the term p A is the amplifying power required by the transmitter to transmit the data, d indicates the distance between i th SU and the CH, and α represents the path loss exponent.…”

“…To mitigate this problem, cognitive radio networks (CRNs) have gained overwhelming recognition in the world of wireless networks in the past. 7 The CRN technology ensures the effective usage of underutilized frequency bands, hence satisfying the ever-increasing needs of IoT applications. [8][9][10] In CRNs, unlicensed/secondary users (SUs) are allowed to access an idle/unused portion (spectrum holes) of the licensed spectrum as long as they do not interfere with the licensed/primary users (PUs).…”

“…The researchers are trying to address the issue of spectrum shortages, which are expected to arise in the future largely because of the ever‐increasing number of wireless applications and devices. To mitigate this problem, cognitive radio networks (CRNs) have gained overwhelming recognition in the world of wireless networks in the past 7 . The CRN technology ensures the effective usage of underutilized frequency bands, hence satisfying the ever‐increasing needs of IoT applications 8–10 …”

A Highly Flexible Passive/Active Discrete-Time Delta-Sigma Receiver

“…Adjusting the signal bandwidth, noise figures, and filtering capability is also required to switch between modes and standards as discussed in [3,4]. Using artificial intelligence has also been explored to optimize the flexibility and performance of receivers [5].…”

Bandpass Sigma–Delta Modulation: The Path toward RF-to-Digital Conversion in Software-Defined Radio

“…The state of the art on ADCs for wireless communications is dominated by three techniques or a combination of them, namely: Sigma-Delta modulators (Σ∆Ms), noise-shaping (NS) SAR and Pipeline. Although wideband Nyquist-rate ADCs-such as SAR, Pipeline or hybrid SAR-Pipeline-are potentially more efficient than Σ∆Ms for digitizing wideband signals, bandpass (BP) Σ∆Ms are, a priori, a better choice for implementing an early RF digitization of the desired signal band/channel in Figure 2b, with a high degree of tunability and adaptability of its performance metrics [17]. Since their conception in 1989 [18,19], a number of BP-Σ∆M ADCs have been reported to implement RF digitizers [16,[20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36].…”