Wireless connectivity will soon enable people to consume augmented and virtual reality content anywhere and cloud-connected mobile robots to perform complex tasks collaboratively. This connectivity will come to enterprises, factory floors and digital homes first, powered by indoor networks that offer much higher data rates, greater reliability, and lower latency than today’s networks. In addition to providing traditional communication capabilities, the future indoor network will have a “sixth sense” that enables it to provide sensory information and insights to meet physiological needs such as lighting, heating, health and safety. It will serve as the core infrastructure for smart buildings and help enterprises operate more efficiently by further enabling capabilities such as immersive virtual workplaces, indoor navigation and asset tracking. This paper reviews current technologies, examines the enabling technologies of the future indoor network and presents our latest research results and our vision for implementing them in commercial and residential environments.

In this paper, we study probabilistic time-of-arrival (ToA) and angle-of-arrival (AoA) joint localization in real indoor environments. To mitigate the effects of multipath propagation, the joint localization algorithm incorporates into the likelihood function Gaussian mixture models (GMM) and the Von Mises-Fisher distribution to model time bias errors and angular uncertainty, respectively. We evaluate the algorithm performance using a proprietary prototype deployed in an indoor factory environment with infrastructure receivers in each of the four corners at the ceiling of a 10 meter by 20 meter section. The field test results show that our joint probabilistic localization algorithm significantly outperforms baselines using only ToA or AoA measurements and achieves 2-D sub-meter accuracy at the 90%-ile. We also numerically demonstrate that the joint localization algorithm is more robust to synchronization errors than the baseline using ToA measurements only.

Despite the large literature on localization, there is no solution yet to localize a commercial off-the-shelf smartphone device using radio measurements from a single WiFi AP. We present SPRING, Smartphone Positioning with Radio measurements from a sINGle wifi access point. SPRING exploits Fine Time Measurements (FTM) and Angle of Arrival (AOA) extracted from commercial chipsets exploiting the specifications of the recent 802.11-2016 and the 802.11ac amendment to combine distance and direction from the AP to the client for positioning. Our system has the potential to bring indoor positioning to homes and small businesses which typically have a single access point. We exploit physical layer (PHY) information to detect the number of paths and their directions. We use this information to derive a new method for filtering ranging measurements obtained with the FTM protocol. We achieve sub-meter distance estimation accuracy eliminating the adverse effect of multipath in FTM using calibrated inputs from Channel State Information (CSI). Our evaluation in indoor scenarios in multipath rich environments demonstrates that the combination of AOA estimation and the proposed FTM refinement approach can locate a Google Pixel 3 smartphone with a median positioning error of 0.9-2.15 m through an area comparable to typical flat sizes.

To statistically model time-variant vehicle-to-vehicle (V2V) channels, the dynamic multi-path components (MPCs) are characterized based on suburban measurements conducted at 5.3 GHz. The correlation matrix distance (CMD) is used to determine the size of local wide-sense stationary (WSS) region. Within each WSS time window, MPCs are extracted using wideband spatial spectrum of Bartlett beamformer. A MPC distance (MCD)-based tracking algorithm is used to identify the "birth" and "death" of MPCs over different WSS regions, and the lifetime of MPC is modeled with a truncated Gaussian distribution. Distributions of number of MPCs and their positions are statistically modeled. The MPC characterization considers both angular and delay domain properties as well as the dynamic evolution of MPCs over different WSS regions. The results shows insight into the dynamic behaviors of MPCs in V2V environments, and is useful for the scatterer modeling in the geometry-based stochastic channel modeling.

This paper presents a measurement-based evaluation of link budget gain from uplink transmit antenna selection in 3GPP LTE. In contrast to earlier studies, the results are based on channel measurements and realistic non-omnidirectional mobile terminal antennas. Further, in addition to the impact of fast selection based on small-scale fading power, also the gain from slow selection based on average signal power is evaluated. In the evaluated measurement cases, fast and slow fading based transmit antenna selection result in up to $3.7$ and $3.2$ dB average power gain, respectively, with respect to the fixed uplink transmit antenna case. This implies that with practical non-omnidirectional terminal antennas a major portion of the gain can be realized based on slow selection, hence justifying a simple open-loop transmit antenna selection scheme which is also applicable to FDD systems.

There has been extensive research about single link multiple-input multiple-output (MIMO) channels, both simulated and measured, but only few studies have targeted multilink analysis with measured channel data. Hence, in this paper, we analyze the influence of spatial separation of user terminals and the human shadowing effect on the MIMO capacity and to the signal to interference ratio (SIR) in a time-variant dual-link scenario. The paper analyses the dual-link channel capacity based on simulations as well as measurements conducted using dynamic dual-link dual-polarized wideband MIMO channel sounder in an indoor office environment, and compare the results to the singlelink capacity. Here the analysis is restricted to 4 x 4 MIMO links. The following conclusions have been obtained from the analyses: 1) Compared to the single link case, the dual-link channel capacity is more affected by the SIR than the spatial separation of the users. 2) The human shadowing introduced variations of SIR up to ±10 dB, causing large fluctuations in the dual-link capacity.

In this paper radio wave scattering processes in an indoor hall environment are reported by analyzing double-directional multiple-input-multiple-output (MIMO) channel sounding data at 5.3 GHz. The pathways and scattering processes of the dominant propagation phenomena were identified using a measurement-based ray tracer (MBRT) software. It is shown that the dominant propagation phenomena included a line-of-sight (LOS) or obstructed LOS component, single, double, and triple bounce scattering processes from walls and ground. The proportion of power carried by each identified pathway was studied. The number of active pathways varied between 3 and 8, which indicates that the multipath environment changes significantly during the measurement route.

This paper aims at validation of an iterative receiver for multiple-input multiple-output with orthogonal frequency division multiplexing (MIMO-OFDM) systems using real-measurement channel data from an indoor scenario. The receiver performs iterative multi-user detection (MUD) and Channel Estimation (CE) via soft information from the single- user decoders. The channel measurements were performed for a dynamic dual MIMO link scenario. The case with two users with multiple antennas interfering each other is considered. CE at the receiver exploits the frequency correlation of the MIMO link. Simulation results for the performance are shown in terms of bit- error rate (BER) vs. signal-to-noise ratio (SNR). Performance for the whole system are provided and compared with respect to the case of perfect channel-state information (PCSI) at the receiver, as well as for the single user. We also provide an analysis of BER with respect to signal-to-interference ratio (SIR). CE performance are evaluated in terms of normalized mean square error (NMSE).

Measurements of car-to-car (C2C) radio channels with 60 MHz bandwidth at 5.3 GHz have been performed in Helsinki, Finland. We focused on 30x30 multiple-input multiple- output (MIMO) measurements, conducted in four environments (urban, sub-urban, campus and highway), under quasi-realistic traffic conditions. As first results, we present in this paper the delay spread statistics for each investigated environment. The largest values of root-mean-square (RMS) delay spread, roughly 2 mus, were obtained in the urban environment. The narrowband channel fading statistics have also been derived using composite distributions, in order to assess the global fading statistics.

This paper presents a comparison between a correlation-based and a ray-based MIMO (multi-input multi-output) model. The correlation-based model has been presented in the literature under the European IST-METRA project. The ray-based model has been elaborated for the 3GPP standard group under the acronym of SCM. Using the input parameters of the 3GPP SCM model specification as a reference, link level simulations results generated from the two MIMO channel models are being compared by examining the channel coefficients and BLER (block error rate) produced by the models. When comparing the simulation results, it was found that the differences between the models are negligible. This implies that either one of the models can be used to generate channel coefficient realizations