相关论文: Transceiver Design with Low-Precision Analog-to-Di…

In this letter, we consider single-cell, single-user systems wherein uplink and downlink user equipment communicate with a full-duplex relay. Due to the near-far problem, the self-interference (SI) can be 100-1000x the received signal…

One way to reduce the power consumption in large-scale multiple-input multiple-output (MIMO) systems is to employ low-resolution analog-to-digital converters (ADCs). In this paper, we investigate antenna selection for large-scale MIMO…

Semantic Communication (SC) is an emerging technology aiming to surpass the Shannon limit. Traditional SC strategies often minimize signal distortion between the original and reconstructed data, neglecting perceptual quality, especially in…

The capacity of a complex and discrete-time memoryless additive white Gaussian noise (AWGN) channel under three constraints, namely, input average power, input amplitude and output delivered power is studied. The output delivered power…

The efficiency of digital nonlinearity compensation (NLC) is analyzed in the presence of noise arising from amplified spontaneous emission noise (ASE) as well as from a non-ideal transceiver subsystem. Its impact on signal-to-noise ratio…

We develop a broadband channel estimation algorithm for millimeter wave (mmWave) multiple input multiple output (MIMO) systems with few-bit analog-to-digital converters (ADCs). Our methodology exploits the joint sparsity of the mmWave MIMO…

In this paper, we investigate secure transmission in a massive multiple-input multiple-output (MIMO) system adopting low-resolution digital-to-analog converters (DACs). Artificial noise (AN) is deliberately transmitted simultaneously with…

In this article, deep learning is applied to estimate the uplink channels for mixed analog-to-digital converters (ADCs) massive multiple-input multiple-output (MIMO) systems, where a portion of antennas are equipped with high-resolution…

RF system-on-chip (RFSoC) devices provide the potential for implementing a complete radio astronomy receiver on a single board, but performance of the integrated analogue-to-digital converters is critical. We have evaluated the performance…

The uplink performance of massive multiple-input-multiple-output (MIMO) systems where the base stations (BS) employ low-resolution analog-to-digital converters (ADCs) is analyzed. A high performance MMSE receiver that takes both additive…

A high-precision charge measurement can be achieved by the area integration of a digitized quasi-Gaussian signal after the signal passes through the shaper and analog-to-digital converter (ADC). The charge measurement contains an error due…

Modern transformer architectures achieve remarkable performance across tasks and domains but remain rigid in how they allocate computation at inference time. Real-world deployment often requires models to adapt to diverse hardware and…

Adaptive Demodulation (ADM) is a newly proposed rate-adaptive system which operates without requiring Channel State Information (CSI) at the transmitter (unlike adaptive modulation) by using adaptive decision region boundaries at the…

The low-snr capacity of M-ary PSK transmission over both the additive white Gaussian noise (AWGN) and fading channels is analyzed when hard-decision detection is employed at the receiver. Closed-form expressions for the first and second…

One of the basic aspects of Massive MIMO (MaMi) that is in the focus of current investigations is its potential of using low-cost and energy-efficient hardware. It is often claimed that MaMi will allow for using analog-to-digital converters…

Nowadays, millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems is a favorable candidate for the fifth generation (5G) cellular systems. However, a key challenge is the high power consumption imposed by its numerous…

Compressed Counting (CC) [22] was recently proposed for estimating the ath frequency moments of data streams, where 0 < a <= 2. CC can be used for estimating Shannon entropy, which can be approximated by certain functions of the ath…

Classical communication paradigms focus on accurately transmitting bits over a noisy channel, and Shannon theory provides a fundamental theoretical limit on the rate of reliable communications. In this approach, bits are treated equally,…

Classical communication paradigms focus on accurately transmitting bits over a noisy channel, and Shannon theory provides a fundamental theoretical limit on the rate of reliable communications. In this approach, bits are treated equally,…

Semantic communication (SemCom) has emerged as a promising paradigm that leverages Deep Neural Networks (DNNs) to extract task-relevant information, thereby substantially reducing the volume of transmitted data. In existing implementations,…