Performance Analysis of Energy-Detection-Based Massive SIMO

Recently, communications systems that are both energy efficient and reliable are under investigation. In this paper, we concentrate on an energy-detection-based transmission scheme where a communication scenario between a transmitter with one antenna and a receiver with significantly many antennas is considered. We assume that the receiver initially calculates the average energy across all antennas, and then decodes the transmitted data by exploiting the average energy level. Then, we calculate the average symbol error probability by means of a maximum a-posteriori probability detector at the receiver. Following that, we provide the optimal decision regions. Furthermore, we develop an iterative algorithm that reaches the optimal constellation diagram under a given average transmit power constraint. Through numerical analysis, we explore the system performance

Non-coherent Massive SIMO Systems in ISI Channels: Constellation Design and Performance Analysis

A massive single-input multiple-output (SIMO) system with a single transmit antenna and a large number of receive antennas in intersymbol interference (ISI) channels is considered. Contrast to existing energy detection (ED)-based non-coherent receiver where conventional pulse amplitude modulation (PAM) is employed, we propose a constellation design which minimizes the symbol-error rate (SER) with the knowledge of channel statistics. To make a comparison, we derive the SERs of the ED-based receiver with both the proposed constellation and PAM, namely $P_{e\_opt}$ and $P_{e\_pam}$. Specifically, asymptotic behaviors of the SER in regimes of a large number of receive antennas and high signal-to-noise ratio (SNR) are investigated. Analytical results demonstrate that the logarithms of both $P_{e\_opt}$ and $P_{e\_pam}$ decrease approximately linearly with the number of receive antennas, while $P_{e\_opt}$ degrades faster. It is also shown that the proposed design is of less cost, because compared with PAM, less antennas are required to achieve the same error rate

Differential data-aided channel estimation for up-link massive SIMO-OFDM

Pilot symbol assisted modulation (PSAM) is widely used to obtain the channel state information (CSI) needed for coherent demodulation. It allows the density of pilot symbols to be dynamically chosen depending on the channel conditions. However, the insertion of pilots reduces the spectral efficiency, more severely when the channel is highly time-variant and/or frequency-selective. In these cases a significant amount of pilots is required to properly track the channel variations in both time and frequency dimensions. Alternatively, non-coherent demodulation does not require any CSI for the demodulation independently of the channel conditions. For the particular case of up-link (UL) based on massive single input -multiple output (SIMO) combined with orthogonal frequency division multiplexing (OFDM), we propose to replace the traditional reference signals of PSAM by a new differentially-encoded data stream that can be non-coherently detected. The latter can be demodulated without the knowledge of the CSI and subsequently used for the channel estimation. We denote our proposal as hybrid demodulation scheme (HDS) because it exploits both the benefits of a coherent demodulation scheme (CDS) and a non-coherent demodulation scheme (NCDS) to increase the spectral efficiency. The mean squared error (MSE) of the channel estimation, bit error rate (BER), achieved throughput and complexity are analyzed to highlight the benefits of this differential data-aided channel estimation as compared to other approaches. We show that the channel estimation is almost as good as PSAM, while the BER performance and throughput are improved for different channel conditions with a very small complexity increase.This work has received funding from the European Union (EU) Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ETN TeamUp5G, grant agreement No. 813391, and from the Spanish National Project TERESA-ADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE)

Design and Performance Analysis of Non-Coherent Detection Systems with Massive Receiver Arrays

Harvesting the gain of a large number of antennas in a mmWave band has mainly been relying on the costly operation of channel state information (CSI) acquisition and cumbersome phase shifters. Recent works have started to investigate the possibility to use receivers based on energy detection (ED), where a single data stream is decoded based on the channel and noise energy. The asymptotic features of the massive receiver array lead to a system where the impact of the noise becomes predictable due to a noise hardening effect. This in effect extends the communication range compared to the receiver with a small number of antennas, as the latter is limited by the unpredictability of the additive noise. When the channel has a large number of spatial degrees of freedom, the system becomes robust to imperfect channel knowledge due to channel hardening. We propose two detection methods based on the instantaneous and average channel energy, respectively. Meanwhile, we design the detection thresholds based on the asymptotic properties of the received energy. Differently from existing works, we analyze the scaling law behavior of the symbol-error-rate (SER). When the instantaneous channel energy is known, the performance of ED approaches that of the coherent detection in high SNR scenarios. When the receiver relies on the average channel energy, our performance analysis is based on the exact SER, rather than an approximation. It is shown that the logarithm of SER decreases linearly as a function of the number of antennas. Additionally, a saturation appears at high SNR for PAM constellations of order larger than two, due to the uncertainty on the channel energy. Simulation results show that ED, with a much lower complexity, achieves promising performance both in Rayleigh fading channels and in sparse channels