Department Publications

Low-resolution analog-to-digital converters (ADCs) are a promising way to cut power consumption in future 6G receivers. However, they break many assumptions behind traditional communication system design. Instead of optimizing each block separately, this work uses an end-to-end autoencoder (AE) to jointly learn and optimize the transmitter and receiver for systems with phase quantization. Two key obstacles arise: (1) phase quantization is non-differentiable, which blocks gradientbased training back to the transmitter, and (2) standard crossentropy loss leads to poor block error rate (BLER) performance. To overcome these issues, we introduce a differentiable approximation of phase quantization and a new loss function that adds a distance-based regularization term to improve symbol separability. Simulations show that the proposed AE achieves near-optimal BLER for uncoded -ary phase shift keying …

Low-resolution digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) are important enablers of energy-efficient wideband uplinks, but they introduce nonlinear distortions whose impact depends on the operating point and, in multi-user systems, on the time- and frequency-resource split. This paper studies quantization-aware uplink resource allocation for multi-user orthogonal multiple access (OMA), focusing on frequency division multiple access (FDMA) and time division multiple access (TDMA) with finite-resolution quantization at both the user transmitters and the base station receiver. Using Bussgang-style decompositions for power-preserving DAC quantization and mid-point ADC quantization, we derive a closed-form, conservative lower bound on the per-user achievable rate in terms of the allocation variables, channel gains, noise level, and quantization distortion factors. Under this …

Noncoherent phase shift keying receivers with coarse phase quantization require one additional bit of phase resolution than their coherent counterparts to achieve full diversity. In this letter, we propose a differential encoding scheme that applies a fixed, resolution-dependent phase shift to the transmitted symbols to remove this identified one-bit performance penalty. The impact of phase quantization on the error performance is characterized under the proposed differential encoding strategy. We show that the proposed differential encoding enables an -bit phase-quantized noncoherent receiver to match the error performance of a conventional -bit phase-quantized noncoherent receiver. Ultimately, our results demonstrate that the one-bit performance penalty previously observed in phase-quantized noncoherent receivers is not a fundamental limitation due to the lack of receiver channel state information, but …

This paper proposes a support vector machine (SVM)-based framework for signal detection in low-resolution single-input multiple-output (SIMO) systems, operating without channel state information (CSI). We consider n-bit phase quantization under M-PSK modulation and develop a CSI-free, model-free detector that directly maps quantized observations to symbol estimates. For QPSK modulation, the proposed method achieves symbol error probability (SEP) performance within 15% of the coherent maximum likelihood detector (MLD). We further extend the framework to higher-order M-PSK modulations, providing the first model-free, CSI-free SEP performance characterization for low-resolution, phase-quantized SIMO systems; addressing a regime where no general MLD solution is available.