This paper presents a closed-form analysis of spatial correlation and degrees of freedom (DoF) for arched holographic multiple-input multiple-output (HMIMO) arrays, which can be viewed as a special form of fluid antenna systems (FAS) when their geometry is fluidically adaptable. Unlike traditional planar configurations, practical HMIMO surfaces may exhibit curvature, significantly influencing their spatial characteristics and performance. We derive exact correlation expressions for both arched uniform linear arrays and arched uniform rectangular arrays, capturing curvature effects under far field propagation. Our results reveal that isotropic scattering results in DoF being dominated by the maximum span of the HMIMO array, such that shape effects are weakened, and bending does not significantly reduce the available spatial DoF. Numerical simulations validate the accuracy of the closed-form formulas and demonstrate the robustness of DoF against curvature variations, supporting flexible array designs. These findings offer fundamental insights into geometry-aware optimization for next-generation HMIMO/FAS systems and pave the way for practical implementations of curved HMIMO arrays.

We investigate the feasibility of using Massive MIMO to support URLLC in both coherence interval based and 3GPP compliant pilot settings. We consider grant-free uplink transmission with MMSE receiver and adopt 3GPP channel models. In the coherence interval based pilot setting, by extensive system level simulations, we find that using a Massive MIMO base station with 128 antennas and MMSE receiver, URLLC requirements can be achieved in Urban Macro (UMa) Non-Line of Sight (NLoS) with orthogonal pilots and Neyman-Pearson detector. However, in the 3GPP compliant pilot setting, even by using the covariance matrix of Physical Resource Block (PRB) subcarriers for active UE detection and channel estimation as well as open-loop power control, we find that URLLC requirements are still challenging to achieve due to the insufficient pilot length and pilot symbol location regulations in a PRB.

An Internet-of-Things (IoT) system supports a massive number of IoT devices wirelessly. We show how to use cell-free (CF) massive multiple input and multiple output (MIMO) to provide a scalable and energy-efficient IoT system. We employ optimal linear estimation with random pilots to acquire channel state information (CSI) for MIMO precoding and decoding. In the uplink (UL), we employ optimal linear decoder and utilize random matrix (RM) theory to obtain two accurate signal-to-interference plus noise ratio (SINR) approximations involving only large-scale fading coefficients. We derive several max–min type power control algorithms based on both exact SINR expression and RM approximations. Next we consider the power control problem for downlink (DL) transmission. To avoid solving a time-consuming quasiconcave problem that requires repeat tests for the feasibility of a second-order cone programming (SOCP) problem, we develop a neural network (NN) aided power control algorithm that results in 30 times reduction in computation time. This power control algorithm leads to scalable CF Massive MIMO networks in which the amount of computations conducted by each access point (AP) does not depend on the number of network APs. Both UL and DL power control algorithms allow visibly improve the system spectral efficiency (SE) and, more importantly, lead to multifold improvements in energy efficiency (EE), which is crucial for IoT networks.

We study internet of things (IoT) systems supported by cell-free (CF) massive MIMO (mMIMO) with optimal linear channel estimation. For the uplink, we consider optimal linear MIMO receiver and obtain an uplink SINR approximation involving only large-scale fading coefficients using random matrix (RM) theory. Using this approximation we design several max-min power control algorithms that incorporate power and rate weighting coefficients to achieve a target rate with high energy efficiency. For the downlink, we consider maximum ratio (MR) beamforming. Instead of solving a complex quasi-concave problem for downlink power control, we employ a neural network (NN) technique to obtain comparable power control with around 30 times reduction in computation time. For large networks we proposed a different NN based power control algorithm. This algorithm is sub-optimal, but its big advantage is that it is scalable.

In a distributed massive multiple-input and multiple-output (DM-MIMO) orthogonal frequency division multiplexing (OFDM) system, each of the multiple receivers receives the OFDM signals simultaneously from all transmitters intended for itself and other receivers. Due to the distributed nature of the network and the differences in propagation delays, these OFDM signals received by any receiver are most likely not synchronized. We have analyzed analytically and numerically the asynchronous reception effects on a DM-MIMO OFDM system in this paper. It is shown that the desired signal power reduction due to phase shifts caused by timing offsets is the dominant performance degrading factor. Surprisingly, the increase of various interfering power (including multiuser, inter-carrier, and inter-symbol interference) due to timing offsets is negligible when compared with the desired signal power reduction. Two per-user rate lower bounds have been developed by averaging over small-scale fading. With the aids of these two lower bounds, averaged per-user rate over small- and large-scale fading have been simulated. It is found that around 50% reduction in per-user downlink rate could occur to the majority of users due to asynchronous reception in DM-MIMO OFDM systems. This important factor needs to be considered in implementing any future DM-MIMO system.

This paper presents a millimeter-wave (mmWave) wideband sliding correlator channel sounder with flexibility to operate at various transmission rates. The channel sounder can transmit and receive up to 1 GHz of RF null-to-null bandwidth while measuring a 2 nanosecond multipath time resolution. The system architecture takes advantage of field-programmable gate arrays (FPGAs), high-speed digital-to-analog converters (DACs), and low phase noise Rubidium (Rb) references for synchronization. Using steerable narrowbeam antennas, the system can measure up to 185 dB of path loss. The channel sounder is used to measure the directional and omnidirectional received power as a receiver transitions from line-of-sight to non-line-of-sight conditions down an urban canyon. A 25 dB drop in omnidirectional received power was observed as the receiver transitioned from line-of-sight (LOS) conditions to deeply shadowed non-LOS (NLOS) conditions. The channel sounder was also used to study signal variation and spatial consistency for a local set of receiver locations arranged in a cluster spanning a 5 m x 10 m local area, where the omnidirectional received power in LOS and NLOS environments is found to be relatively stable with standard deviations of received power of 2.2 dB and 4.3 dB, respectively. This work shows that when implementing beamforming at the transmitter at mmWave, the omnidirectional received power over a local area has little fluctuation among receiver locations separated by a few to several meters.

This paper presents outdoor wideband small-scale spatial fading and autocorrelation measurements and results in the 73 GHz millimeter-wave (mmWave) band conducted in downtown Brooklyn, New York. Both directional and omnidirectional receiver (RX) antennas are studied. Two pairs of transmitter (TX) and RX locations were tested with one line-of-sight (LOS) and one non-line-of-sight (NLOS) environment, where a linear track was employed at each RX to move the antenna in half-wavelength increments. Measured data reveal that the small-scale spatial fading of the received signal voltage amplitude are generally Ricean-distributed for both omnidirectional and directional RX antenna patterns under both LOS and NLOS conditions in most cases, except for the log-normal distribution for the omnidirectional RX antenna pattern in the NLOS environment. Sinusoidal exponential and typical exponential functions are found to model small-scale spatial autocorrelation of the received signal voltage amplitude in LOS and NLOS environments in most cases, respectively. Furthermore, different decorrelation distances were observed for different RX track orientations, i.e., for different directions of motion relative to the TX. Results herein are valuable for characterizing small-scale spatial fading and autocorrelation properties in multiple-input multiple-output (MIMO) systems for fifth-generation (5G) mmWave frequencies.