This article introduces a digital conversion and linearization unit (DCLU) that performs signal conversion and power amplifier (PA) linearization when the digital-to-analog converter (DAC) is constrained by limited bit resolution. The proposed structure applies an error-and-distortion-feedback (EDF) processing principle that integrates re-quantization, noise shaping, and digital predistortion (DPD) within a single digital unit and avoids explicit inverse modeling. The embedded PA forward description uses a polar look-up table (PLUT) representation of the PA static AM/AM and AM/PM characteristics and a linear filter that captures the measured dynamic response. More advanced approaches are also described in terms of incorporating more elaborate forward models within the DCLU, together with a parallel multi-channel realization that relaxes internal clock-rate requirements through time-interleaved processing. The concept is validated through two RF measurement experiments using a 5G New Radio (NR) transmit waveform at 3.5 GHz and 3.6 GHz (NR band n78). The first experiment uses a broadband Gallium-Nitride (GaN) HMC1114 PA to demonstrate the proof of concept and quantify system behavior under reduced bit resolutions. The second experiment uses the Qorvo QPA3503 GaN Doherty PA to evaluate the approach for an amplifier type that is typically more challenging to linearize. The measured results show that the proposed approach maintains good linearization capability under reduced bit resolutions and, in the reported cases, provides improved transmit waveform quality relative to conventional reference DPD schemes, particularly at lower bit widths.

In this article, we address the timely topic of cellular bistatic simultaneous localization and mapping (SLAM) with specific focus on end-to-end processing solutions, from raw I/Q samples, via channel parameter estimation to user equipment (UE) and landmark location information in millimeter-wave (mmWave) networks, with minimal prior knowledge. Firstly, we propose a new multipath channel parameter estimation solution that operates directly with beam reference signal received power (BRSRP) measurements, alleviating the need to know the true antenna beampatterns or the underlying beamforming weights. Additionally, the method has built-in robustness against unavoidable antenna sidelobes. Secondly, we propose new snapshot SLAM algorithms that have increased robustness and identifiability compared to prior art, in practical built environments with complex clutter and multi-bounce propagation scenarios, and do not rely on any a priori motion model. The performance of the proposed methods is assessed at the 60GHz mmWave band, via both realistic ray-tracing evaluations as well as true experimental measurements, in an indoor environment. A wide set of offered results demonstrate the improved performance, compared to the relevant prior art, in terms of the channel parameter estimation as well as the end-to-end SLAM performance. Finally, the article provides the measured 60GHz data openly available for the research community, facilitating results reproducibility as well as further algorithm development.

In this article, we propose a new robust and highly efficient digital predistortion (DPD) concept for the linearization of wideband RF power amplifiers (PAs). The proposed approach is based on the combination of a parallelized delta-sigma modulator (DSM) and a forward model of the PA. This concept applies multi-rate techniques on a DSM that incorporates the forward PA model in its feedback loop to perform the required signal predistortion. Such a technique eliminates the need of reverse modeling and its associated problems. The multi-rate approach relaxes enormously the clock speed requirement of the DPD, which allows handling high signal bandwidths at feasible sampling rates. Moreover, enhanced performance can be achieved without the need of increasing the order of the modulator which reduces the sensitivity of the system to gain variations and phase distortions caused by the nonlinear PA characteristics. Three time-interleaved parallel DPD (P-DPD) variants are described and introduced, all of them have been shown to offer increased accuracy, and consequently better linearization performance compared to the DSM-based DPD state-of-the-art. The proposed architectures are tested and assessed using extensive real-world RF measurements at the 3.6 GHz band utilizing wideband 100 MHz 5G New Radio (NR) transmit waveforms, evidencing excellent transmit signal quality.

In this paper, new digital predistortion (DPD) solutions for power amplifier (PA) linearization are proposed, with particular emphasis on reduced processing complexity in future 5G and beyond wideband radio systems. The first proposed method, referred to as the spline-based Hammerstein (SPH) approach, builds on complex spline-interpolated lookup table (LUT) followed by a linear finite impulse response (FIR) filter. The second proposed method, the spline-based memory polynomial (SMP) approach, contains multiple parallel complex spline-interpolated LUTs together with an input delay line such that more versatile memory modeling can be achieved. For both structures, gradient-based learning algorithms are derived to efficiently estimate the LUT control points and other related DPD parameters. Large set of experimental results are provided, with specific focus on 5G New Radio (NR) systems, showing successful linearization of multiple PA samples as well as a 28 GHz active antenna array, incorporating channel bandwidths up to 200 MHz. Explicit performance-complexity comparisons are also reported between the SPH and SMP DPD systems and the widely-applied ordinary memory-polynomial (MP) DPD solution. The results show that the linearization capabilities of the proposed methods are very close to that of the ordinary MP DPD, particularly with the proposed SMP approach, while having substantially lower processing complexity.

In this paper, we present a novel nonlinear digital self-interference canceller algorithm, its implementation details on a software-defined radio (SDR) platform, and performance results of real-time full-duplex experiments on both device and link level. The canceller algorithm is based on an augmented Hammerstein model, with a nonlinear part modeling the transmitter non-idealities followed by a linear filter to model the self-interference (SI) channel. The nonlinear part includes a spline-based model for the nonlinear power amplifier, a polynomial model for baseband nonlinearities, as well as models for I/Q mismatch and LO leakage. The canceller is implemented on an FPGA as a part of an OFDM transceiver testbed for real-time measurements. Extensive real-time measurements show excellent performance: (1) the digital canceller, together with an RF isolator, can suppress the SI to within 1-2 dB's of the receiver noise floor, with total SI suppression of up to 103 dB; (2) digital cancellation of up to 46 dB is evidenced, which is among the highest real-time cancellations in literature; (3) system-level measurements with OFDM signals demonstrate the benefit of utilizing the proposed canceller in a two-way communication scenario, showing up to 90 % increase in sum-rate compared to half-duplex communication.

The emerging full-duplex (FD) radio concept is set to double the spectral efficiency of commercial wireless networks, but it also has potential applications in the defense and security domains. In the form of multifunction military full-duplex radios (MFDRs), the FD capability could enable armed forces to conduct simultaneous electronic attacks, electronic support measures, and tactical communications. This paper demonstrates the feasibility of simultaneous jamming and reconnaissance of drones' remote control (RC) systems using a prototype MFDR. Alongside, we apply deep learning in the form of a convolutional neural network (CNN) for classifying the RC signals and analyze the effect of FD operation on the classification performance.

Inband full-duplex (IBFD) technology enables radios to simultaneously transmit and receive (STAR) on the same frequencies with the benefit of, e.g., enhanced spectral efficiency in non-military communications. In addition, there is significant potential in the IBFD concept in military applications as currently conventional time-or frequency-division half-duplex radios are used in all military applications. A military full-duplex radio (MFDR) would be capable of simultaneous integrated tactical communication and electronic warfare operations. This paper presents an application where an MFDR enables the user to successfully detect an electronic attack, i.e., jamming from an adversary, while simultaneously transmitting tactical transmissions to an ally on the same frequency channel. Successful detection enables the MFDR to gather intelligence and take countermeasures against the jamming, e.g., switching to a different carrier frequency. The experimental results reported herein prove that the radio is able to reliably detect the presence of jamming for received jamming signal powers down to -95 dBm while simultaneously transmitting to an ally at 10-dBm power level. Therefore, the full-duplex radio can give armed forces a significant technical lead over an enemy by detecting enemy jamming even when the adversary only transmits jamming during friendly transmissions.