Massive MIMO is a reality—What is next?: Five promising research directions for antenna arrays

Location information for events, assets, and individuals, mostly focusing on two dimensions so far, has triggered a multitude of applications across different verticals, such as consumer, networking, industrial, health care, public safety, and emergency response use cases. To fully exploit the potential of location awareness and enable new advanced location-based services, localization algorithms need to be combined with complementary technologies including accurate height estimation, i.e., three dimensional location, reliable user mobility classification, and efficient indoor mapping solutions. This survey provides a comprehensive review of such enabling technologies. In particular, we present cellular localization systems including recent results on 5G localization, and solutions based on wireless local area networks, highlighting those that are capable of computing 3D location in multi-floor indoor environments. We overview range-free localization schemes, which have been traditionally explored in wireless sensor networks and are nowadays gaining attention for several envisioned Internet of Things applications. We also present user mobility estimation techniques, particularly those applicable in cellular networks, that can improve localization and tracking accuracy. Regarding the mapping of physical space inside buildings for aiding tracking and navigation applications, we study recent advances and focus on smartphone-based indoor simultaneous localization and mapping approaches. The survey concludes with service availability and system scalability considerations, as well as security and privacy concerns in location architectures, discusses the technology roadmap, and identifies future research directions.

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

As the standardization of 5G solidifies, researchers are speculating what 6G will be. The integration of sensing functionality is emerging as a key feature of the 6G Radio Access Network (RAN), allowing for the exploitation of dense cell infrastructures to construct a perceptive network. In this IEEE Journal on Selected Areas in Communications (JSAC) Special Issue overview, we provide a comprehensive review on the background, range of key applications and state-of-the-art approaches of Integrated Sensing and Communications (ISAC). We commence by discussing the interplay between sensing and communications (S&C) from a historical point of view, and then consider the multiple facets of ISAC and the resulting performance gains. By introducing both ongoing and potential use cases, we shed light on the industrial progress and standardization activities related to ISAC. We analyze a number of performance tradeoffs between S&C, spanning from information theoretical limits to physical layer performance tradeoffs, and the cross-layer design tradeoffs. Next, we discuss the signal processing aspects of ISAC, namely ISAC waveform design and receive signal processing. As a step further, we provide our vision on the deeper integration between S&C within the framework of perceptive networks, where the two functionalities are expected to mutually assist each other, i.e., via communication-assisted sensing and sensing-assisted communications. Finally, we identify the potential integration of ISAC with other emerging communication technologies, and their positive impacts on the future of wireless networks. 

/pdf/integrated-sensing-and-communications-toward-dual-functional-sob6jd9u.pdf

Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond

The very last wireless network technology, created to increase the speed and the connections responsiveness, the Fifth-Generation Network (5G) can transmit a great volume of data It uses wireless broadband connections to support specific end-users and businesses services It is specifically useful for the Internet of Vehicles (IoV), guaranteeing fast connections and security The 5G network technology can be used to support Vehicle-to-Everything (V2X) communications and applications on autonomous vehicles It can enable information exchanges between vehicles and other infrastructures and people It can also provide a more comfortable and safer environment and accurate traffic knowledge The traffic ?ow can be improved, reducing pollution and accident rates The cellular network can be associated with V2X as a communicating base to offer enhanced road safety and autonomous driving, and also to offer the IoV connections This survey presents the 5G technology evolution, standards, and infrastructure associated with V2X ecosystem by IoV In other words, it presents the IoV supported by 5G V2X communications, considering its architecture, applications and also the V2X features and protocols, as well as the modes, the evaluation and the technological support in such combination The contribution of this paper is a systematized study about the interaction among these three contents: IoV, 5G, and V2X Eighty four works were selected to present concepts, standards and to identify the ways to overcome challenges This survey aims to guide the development of new 5G-V2X services and technologies dedicated to vehicle communications, and also to indicate future directions

/pdf/a-survey-of-5g-technology-evolution-standards-and-3vw1b5bn73.pdf

A Survey of 5G Technology Evolution, Standards, and Infrastructure Associated With Vehicle-to-Everything Communications by Internet of Vehicles

5G millimeter wave (mmWave) signals can enable accurate positioning in vehicular networks when the base station and vehicles are equipped with large antenna arrays. However, radio-based positioning suffers from multipath signals generated by different types of objects in the physical environment. Multipath can be turned into a benefit, by building up a radio map (comprising the number of objects, object type, and object state) and using this map to exploit all available signal paths for positioning. We propose a new method for cooperative vehicle positioning and mapping of the radio environment, comprising a multiple-model probability hypothesis density filter and a map fusion routine, which is able to consider different types of objects and different fields of views. Simulation results demonstrate the performance of the proposed method.

/pdf/5g-mmwave-cooperative-positioning-and-mapping-using-multi-1z7m1ossnw.pdf

5G mmWave Cooperative Positioning and Mapping Using Multi-Model PHD Filter and Map Fusion

5G new radio (NR) provides new opportunities for accurate positioning from a single reference station: large bandwidth combined with multiple antennas, at both the base station and user sides, allows for unparalleled angle and delay resolution. Nevertheless, positioning quality is affected by multipath and clock biases. We study, in terms of performance bounds and algorithms, the ability to localize a vehicle in the presence of multipath and unknown user clock bias. We find that when a sufficient number of paths is present, a vehicle can still be localized thanks to redundancy in the geometric constraints. Moreover, the 5G NR signals enable a vehicle to build up a map of the environment.

/pdf/5g-mm-wave-downlink-vehicular-positioning-4mla5tkml2.pdf

5G mm Wave Downlink Vehicular Positioning

5G communication systems operating above 24 GHz have promising properties for user localization and environment mapping. Existing studies have either relied on simplified abstract models of the signal propagation and the measurements, or are based on direct positioning approaches, which directly map the received waveform to a position. In this study, we consider an intermediate approach, which consists of four phases-downlink data transmission, multi-dimensional channel estimation, channel parameter clustering, and simultaneous localization and mapping (SLAM) based on a novel likelihood function. This approach can decompose the problem into simpler steps, thus leading to lower complexity. At the same time, by considering an end-to-end processing chain, we are accounting for a wide variety of practical impairments. Simulation results demonstrate the efficacy of the proposed approach.

/pdf/5g-slam-using-the-clustering-and-assignment-approach-with-2rl1umbuvh.pdf

5G SLAM Using the Clustering and Assignment Approach with Diffuse Multipath

Vehicle positioning based on GPS is limited due to multipath and blockage. 5G mmWave signals can provide an attractive complement, as it is possible to estimate the state of a vehicle (position and heading) from transmissions from a single base station. We propose a Bayesian 5G mmWave tracking filter, which explicitly relies on mapping the radio environment. The filter thus solves a novel type of simultaneous localization and mapping problem, which enables estimating not only the vehicle heading and position, but also its clock bias.

/pdf/5g-mmwave-vehicular-tracking-27k3pbjsaf.pdf

5G mmWave Vehicular Tracking

This paper presents a cooperative localization strategy via a distributed optimization technique known as the alternating direction method of multipliers (ADMM). In a Vehicular Ad hoc Network (VANET) where a vehicle communicates with neighboring vehicles via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, the developed algorithm utilizes three types of measurements, which are the pairwise relative distance, angle of arrival, and absolute positions for a subset of vehicles in cooperative localization. The proposed algorithm is designed to provide an attractive solution for the localization of autonomous driving vehicle in the GPS-denied (urban) environment. Simulation results confirm the potency of distributed ADMM-based cooperative localization for autonomous driving in 5G-based VANETs.

Hyowon Kim

Papers

5G mmWave Cooperative Positioning and Mapping Using Multi-Model PHD Filter and Map Fusion

5G mm Wave Downlink Vehicular Positioning

5G SLAM Using the Clustering and Assignment Approach with Diffuse Multipath

5G mmWave Vehicular Tracking

Cooperative localization with distributed ADMM over 5G-based VANETs