The Downlink Performance for Cell-Free Massive MIMO with Instantaneous CSI in Slowly Time-Varying Channels

In centralized massive multiple-input multiple-output (MIMO) systems, the channel hardening phenomenon can occur, in which the channel behaves as almost fully deterministic as the number of antennas increases. Nevertheless, in a cell-free massive MIMO system, the channel is less deterministic. In this paper, we propose using instantaneous channel state information (CSI) instead of statistical CSI to obtain the power control coefficient in cell-free massive MIMO. Access points (APs) and user equipment (UE) have sufficient time to obtain instantaneous CSI in a slowly time-varying channel environment. We derive the achievable downlink rate under instantaneous CSI for frequency division duplex (FDD) cell-free massive MIMO systems and apply the results to the power control coefficients. For FDD systems, quantized channel coefficients are proposed to reduce feedback overhead. The simulation results show that the spectral efficiency performance when using instantaneous CSI is approximately three times higher than that achieved using statistical CSI.

Fabrication and microfluidic analysis of graphene-based molecular communication receiver for Internet of Nano Things (IoNT)

Bio-inspired molecular communications (MC), where molecules are used to transfer information, is the most promising technique to realise the Internet of Nano Things (IoNT), thanks to its inherent biocompatibility, energy-efficiency, and reliability in physiologically-relevant environments. Despite a substantial body of theoretical work concerning MC, the lack of practical micro/nanoscale MC devices and MC testbeds has led researchers to make overly simplifying assumptions about the implications of the channel conditions and the physical architectures of the practical transceivers in developing theoretical models and devising communication methods for MC. On the other hand, MC imposes unique challenges resulting from the highly complex, nonlinear, time-varying channel properties that cannot be always tackled by conventional information and communication tools and technologies (ICT). As a result, the reliability of the existing MC methods, which are mostly adopted from electromagnetic communications and not validated with practical testbeds, is highly questionable. As the first step to remove this discrepancy, in this study, we report on the fabrication of a nanoscale MC receiver based on graphene field-effect transistor biosensors. We perform its ICT characterisation in a custom-designed microfluidic MC system with the information encoded into the concentration of single-stranded DNA molecules. This experimental platform is the first practical implementation of a micro/nanoscale MC system with nanoscale MC receivers, and can serve as a testbed for developing realistic MC methods and IoNT applications.

Joint Channel Tracking and Data Detection for Massive MIMO Uplink Over Time-Varying Channel

In this letter, we propose a novel joint channel estimation and data detection scheme for massive multiple-input multiple-output (MIMO) uplink, which operates in a time-varying fading channel. More specifically, at the receiver of the proposed scheme, a data frame is divided into multiple blocks, and in each block, a demodulated data block is used for updating channel state information (CSI) in an iterative manner. Furthermore, the initial CSI in the block of interest is given by the estimated CSI in the previous block, hence allowing accurate tracking of CSI in a time-varying channel without imposing additional pilot insertion inside the data frame. Since the length of the divided blocks affects both the achievable channel tracking and data detection performances, it is optimized so as to maximize the discrete-input continuous-output memoryless channel's (DCMC) capacity derived in this letter. It is demonstrated that the DCMC capacity of the proposed scheme is capable of nearly achieving those of the perfect CSI counterpart without imposing any substantial pilot overhead.

Joint Channel Tracking and Data Detection for Massive MIMO Uplink Over Time-Varying Channel

In this letter, we propose a novel joint channel estimation and data detection scheme for massive multiple-input multiple-output (MIMO) uplink, which operates in a time-varying fading channel. More specifically, at the receiver of the proposed scheme, a data frame is divided into multiple blocks, and in each block, a demodulated data block is used for updating channel state information (CSI) in an iterative manner. Furthermore, the initial CSI in the block of interest is given by the estimated CSI in the previous block, hence allowing accurate tracking of CSI in a time-varying channel without imposing additional pilot insertion inside the data frame. Since the length of the divided blocks affects both the achievable channel tracking and data detection performances, it is optimized so as to maximize the discrete-input continuous-output memoryless channel's (DCMC) capacity derived in this letter. It is demonstrated that the DCMC capacity of the proposed scheme is capable of nearly achieving those of the perfect CSI counterpart without imposing any substantial pilot overhead.