Millimeter-Wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation

5G New Radio (NR) is the 3rd Generation Partnership Project (3GPP) radio access technology for the next generation mobile communications network. A major evolution of 5G constitutes the integration of non-terrestrial networks including geostationary and low Earth orbit satellites. The seamless integration of satellites in the terrestrial mobile network requires significant adaptations within the radio access network and the development of new features in the core network to cope with the specific satellite channel characteristics. To date, the 5G control and data plane has been standardized to handle only continuous backhaul communication between the network components. However, a mobile satellite enabled next generation Node B (gNB) located in a vehicle or in a moving aerial platform needs to be able to handle frequent backhaul outages of various duration as well as longer signal delays as opposed to short terrestrial connections via fiber. In this paper, we report the results of an over-the-air (OTA) field trial comprising a mobile edge node connected to the 5G standalone core network components over a geostationary satellite. We analyze Transmission Control Protocol (TCP) acceleration and GPRS Tunneling Protocol (GTP)/TCP/Internet Protocol (IP) header compression features through the GTP. Moreover, the influence of short and long interruptions in the communication between the edge node and the central components on the entire system performance is investigated. The header compression and TCP acceleration modules were implemented on the satellite modems and are now part of the protocol stack of these devices. The results show up to 12% higher data rates for the 5G user equipment (UE), on a 1.5 MHz single carrier return link compared to deactivated TCP acceleration and header compression. We increased the data rate by 20% on the 4.5 MHz DVB-S2X forward link between the UE and 5G core. Moreover, our measurements reveal that even satellite-enabled gNB mobility is possible with the current Release 15 standard. After a short outage of the satellite connection due to shadowing, the UE can successfully re-establish the user plane connection to the core network. Our results will facilitate the full integration of satellite components in 5G through open and standard solutions.

Bandwidth Parts (BWPs) is a 5G New Radio (NR) Release 15 feature introduced for dynamically adapting the carrier bandwidth and numerology in which a User Equipment (UE) operates. In 4G/LTE, UEs support the maximum possible bandwidth of 20MHz. In 5G, the operating bandwidth can be as high as 800MHz per carrier. Each UE cannot support such a high bandwidth without high-power consumption. Therefore, a 5G UE has to communicate on a bandwidth smaller than the cell’s channel bandwidth. The smaller part is referred to as BWP. BWP enables higher spectrum flexibility with reduced baseband processing and power savings. BWP selection (or BWP switching) can be performed through several different methods. bwp-InactivityTimer is one of the methods or techniques to switch BWP. BWP switching is always associated with switch delay. Frequent BWP switching directly impacts latency and system throughput. In NR, new gap patterns with larger gap lengths of 40 ms and 66 ms features are implemented for accurate positioning measurements. The effect of bwp-InactivityTimer during larger measurement gaps and associated delays have not been studied and understood thoroughly for bursty traffic. Trade-offs must be carefully considered between energy efficiency and other performance aspects such as latency, throughput, and so on. In this paper, we propose an Efficient BWP Switch Method (EBSM) novel algorithm to handle bwp-InactivityTimer to reduce latency and thereby increase the system throughput during larger gap lengths configured for accurate positioning measurements. Simulation results show that the proposed EBSM algorithm is on average 29.8% more efficient in shortening latency and around 15-52% more efficient in avoiding unnecessary BWP switching in comparison with the specification-defined current legacy method.

The emerging 5G New Radio (NR) networks will provide large improvements in mobile radio access in terms of peak data rates, latency, reliability and network capacity. One of the new technical elements compared to LTE-based networks is the support for millimeter-wave (mmW) frequencies, facilitating carrier bandwidths up to 400 MHz at the currently specified operating bands between 24–40 GHz. Such large bandwidths enable highly-accurate time-based measurements and hence ranging. Thus, in time-division duplexing (TDD) based networks, base-stations and possibly also user equipment can pursue high-accuracy radio sensing by observing the transmit signal reflections, assuming that the direct transmitter-receiver leakage or self-interference can be sufficiently suppressed. In this article, we address, analyze and demonstrate the prospects of OFDM-waveform based radio sensing in 5G NR base-stations with particular emphasis on the mmW use cases. First, basic target range and velocity estimation resolution analysis is provided for different carrier bandwidths and observation time windows, showing that close to centimeter-level ranging accuracy can basically be obtained. Then, specific emphasis is put on the analysis and suppression of the direct self-interference when executing the receiver simultaneously to transmitting. Finally, concrete RF measurements at 28 GHz operating band are provided and analyzed comprising self-interference cancellation and radar processing solutions. The obtained results demonstrate that direct self-interference cancellation can be successfully carried out, and that targets can be accurately sensed and tracked.

The 3rd generation partnership project (3GPP) has recently specified the non-standalone 5G New Radio (NR), in which the dual connectivity (DC) feature plays an essential role. A User Equipment (UE) with DC is able to concurrently connect to an evolved NodeB (eNB) (e.g., using LTE in a macro cell) and a next generation NodeB (gNB) (e.g., using 5G NR in a small cell) aiming to satisfy the 5G's required Key Performance Indicators (KPIs). In this work, we focus on the issue of concurrent transmissions on the 5G small cell, which potentially exploit the benefits of DC. With DC, an application is able to spread its traffic over different two paths (via eNB and gNB) between the UE and the LTE core network. The traffic over diverse paths may experience different delay since the conditions are generally different (e.g., due to wireless channel, background traffic). Therefore, one of the most important problems in efficient operation with DC is minimizing the end-to-end delay considering all the connections. To address that problem, we adopt the deterministic network calculus to first characterize the delay experienced by each connection; then to model the overall end-to- end delay in the 5G small cell. We then formulate an optimization problem that attempts to find the optimal traffic splitting over the connections while minimizing the delay. We derive the solution for the problem, as well as, present the numerical results.

Purpose of software-defined radio (SDR) network positioning technology design is substantiation and experimental validation of new technical solutions for user equipment (UE) location estimation improvement, using infrastructure of existing 4G Long-Term Evolution (LTE) and emerging 5G New Radio (NR) networks, which is highly relevant in Global Navigation Satellite System (GNSS) denied urban environments. Approach for experimental validation is prototyping of eNodeB (eNB) reference signals transmission and UE reception procedures using SDR testbed with Universal Software Radio Peripheral (USRP) hardware and Matlab software. Generation and transmission of reference signals, performed by eNB on the physical layer, is defined by 3GPP technical specification 36.211, and receiver processing procedures, performed by UE, and strongly affecting the accuracy of primary measurements, can be designed as a proprietary solution. Findings of current research include formalization, software realization and results of experimental validation of a sequence of procedures for receiving and processing LTE reference signals in order to collect primary range-difference measurements on the UE side for observed time difference of arrival (OTDOA) positioning with developed SDR testbed. Research and development campaign on the current stage has limitation of SDR testbed validation only in laboratory conditions. Practical implications of developed UE SDR testbed allow to proceed campaign to the field conditions and test proposed technical solution with ambient LTE signals.

The recommended bit rate (RBR) is assigned by gNodeB to the user equipment (UE) using MAC control element (CE) entity to provide bit rate information in 5G New Radio (NR). At the UE, the bit rate information is passed on to the upper layers; i.e., transport or application, for a specific logical channel either in uplink or downlink. However, based on specific application rate of target, UE does not know how to efficiently utilize and distribute RBR/throughput in lower and upper layer, respectively considering the specific logical channel. To address these problems, we propose a cross layer rate adaptation (CLRA) mechanism for UE. CLRA consists of two parts. In the first part, CLRA utilizes RBR received from gNodeB to compute throughput at lower layer. In the second part, CLRA distributes the throughput in upper layer received from lower layer based on specific applications rate of target. CLRA provides an intelligent mechanism to distribute throughput among foreground/ background applications and voice over internet protocol (VoIP) application considering a learning based codec adaptation. We conduct experiments with Samsung Galaxy S8 device and simulations to validate CLRA mechanism for applications in 5G NR.

The emerging 5G New Radio (NR) networks are expected to enable huge improvements, e.g., in terms of capacity, number of connected devices, peak data rates and latency, compared to existing networks. At the same time, a new trend referred to as the RF convergence is aiming to jointly integrate communications and sensing functionalities into the same systems and hardware platforms. In this paper, we investigate the sensing prospects of 5G NR systems, with particular emphasis on the user equipment side and their potential for joint communications and environment mapping. To this end, a radio-based sensing approach utilizing the 5G NR uplink transmit signal and an efficient receiver processing and mapping scheme are proposed. An indoor scenario is then studied and evaluated through real-world RF measurements at 28 GHz mm-wave band, showing that impressive mapping performance can be achieved by the proposed system. The measurement data is available at a permanent open repository.

This paper proposes an evaluation of the performance of 5G communication between a user equipment (UE), which can be a car, and a 5G base station (gNB), under the influence of different numbers of UEs connected to that base station. There are two approaches to this communication evaluation: i) simulated mode, using Simu5G, which is a simulator for 5G New Radio (NR) networks; ii) a practical way using a hardware setup defined on the basis of a SIM8200EA-M2 module in order to test a real-life scenario. Various performance indicators are tracked and also compared, such as Signal-to-interference-plus-noise ratio (SINR), Channel Quality Indicator (CQI), and End-to-End (E2E) Delay in order to analyze the effect of network load on 5G communication between the UE and gNB.

The Dual connectivity (DC) technology is a robust solution for Internet service providers (ISP) to evolve their legacy infrastructures with less cost to speed up the progress of fifth-generation (5G) services coverage. DC enables the traditional network to connect to multiple New Radio (NR) Node B (gNBs). A well-known scheme is the non-standalone (NSA) NR. In this case, the user equipment (UEs) could access the network via both the evolved Node B (eNB) and the gNB. However, some research has indicated that the UEs in such a configuration suffer from power consumption problems. UEs are typically configured with discontinuous reception (DRX) mechanism to save power. However, most current systems do not investigate and optimize the DRX parameters. To the authors’ best knowledge, this work is the first to combine DRX with traffic steering for the UEs in the NSA NR system. A traffic steering algorithm is proposed to improve the coordination between the eNB and the gNB. We used a semi-Markov chain model to analyze power consumption and average delay. Compared with standard DRX operated in LTE, NR, and DC, we verified that the proposed model achieves power-saving gains without incurring an additional delay. The results indicated that the UE could save considerable power with an optimized system configuration.

Adaptive interacting multiple model for underwater maneuvering target tracking with one-step randomly delayed measurements

The evolution of communication networks has witnessed a remarkable transformation with the advent of 5G technology. As the latest generation of cellular networks, 5G promises to revolutionize the way we connect, communicate, and interact with the digital world. This paper explores the architecture, management, and implications of 5G communication networks, shedding light on the key features, challenges, and opportunities presented by this transformative technology. At the core of 5G networks lies a sophisticated architecture designed to deliver unprecedented levels of speed, reliability, and connectivity. The 5G New Radio (NR) architecture encompasses three primary components: the User Equipment (UE), the Radio Access Network (RAN), and the Core Network (CN). These components work in tandem to facilitate seamless communication between user devices and the broader network infrastructure. One of the defining features of 5G networks is their ability to support significantly higher data speeds and lower latency compared to previous generations. With the potential to deliver data rates of several gigabits per second and latency as low as a few milliseconds, 5G opens the door to a plethora of innovative applications and services, ranging from immersive virtual reality experiences to real-time remote surgeries. Effective management of 5G networks is paramount to ensuring optimal performance, reliability, and security. Network management systems employ advanced algorithms for dynamic resource allocation, quality of service (QoS) optimization, and network slicing. Network slicing, in particular, enables operators to create virtual networks tailored to specific use cases, such as enhanced mobile broadband, massive IoT deployments, and mission-critical communications. However, the deployment and management of 5G networks pose several challenges and considerations. Infrastructure deployment requires substantial investment and coordination, while ensuring interoperability between different vendors' equipment and standards remains a pressing issue. Spectrum availability and allocation also play a critical role in determining the performance and capacity of 5G networks, necessitating careful regulatory oversight and spectrum management strategies. Despite these challenges, the implications of 5G technology are far-reaching and profound. From empowering smart cities and autonomous vehicles to enabling the widespread adoption of IoT devices and applications, 5G networks have the potential to reshape industries, drive innovation, and enhance the quality of life for billions of people around the world. 5G communication networks represent a paradigm shift in the way we connect and communicate. With their advanced architecture, dynamic management capabilities, and transformative potential, 5G networks are poised to unlock new opportunities, accelerate digital transformation, and usher in a new era of connectivity and innovation.

Time-varying channel is an important characteristic of a mobile communication system, which will cause random fluctuations of the quality of received signal at the user equipment (UE). Link adaptation is one of the key technologies to deal with the variant channel condition. It maximizes the data transmission rate over a limited bandwidth. In this paper, we design and implement an end-to-end link-adaptive system based on the 5G New Radio (NR) standard, adopting software defined radio (SDR) equipment as the baseband processing module. In the designed system, the selection of channel quality information (CQI) and the link-adaptive module are implemented at the base station (BS). The design and implementation of the physical layer according to 5G NR standard, including system parameters, synchronization scheme and duplex mode, are provided. Further, the over-the-air (OTA) results validate the feasibility of the system design, and show that link adaptation module can significantly improve the quality of the received signal.

The evolution of communication networks has witnessed a remarkable transformation with the advent of 5G technology. As the latest generation of cellular networks, 5G promises to revolutionize the way we connect, communicate, and interact with the digital world. This paper explores the architecture, management, and implications of 5G communication networks, shedding light on the key features, challenges, and opportunities presented by this transformative technology. At the core of 5G networks lies a sophisticated architecture designed to deliver unprecedented levels of speed, reliability, and connectivity. The 5G New Radio (NR) architecture encompasses three primary components: the User Equipment (UE), the Radio Access Network (RAN), and the Core Network (CN). These components work in tandem to facilitate seamless communication between user devices and the broader network infrastructure. One of the defining features of 5G networks is their ability to support significantly higher data speeds and lower latency compared to previous generations. With the potential to deliver data rates of several gigabits per second and latency as low as a few milliseconds, 5G opens the door to a plethora of innovative applications and services, ranging from immersive virtual reality experiences to real-time remote surgeries. Effective management of 5G networks is paramount to ensuring optimal performance, reliability, and security. Network management systems employ advanced algorithms for dynamic resource allocation, quality of service (QoS) optimization, and network slicing. Network slicing, in particular, enables operators to create virtual networks tailored to specific use cases, such as enhanced mobile broadband, massive IoT deployments, and mission-critical communications. However, the deployment and management of 5G networks pose several challenges and considerations. Infrastructure deployment requires substantial investment and coordination, while ensuring interoperability between different vendors' equipment and standards remains a pressing issue. Spectrum availability and allocation also play a critical role in determining the performance and capacity of 5G networks, necessitating careful regulatory oversight and spectrum management strategies. Despite these challenges, the implications of 5G technology are far-reaching and profound. From empowering smart cities and autonomous vehicles to enabling the widespread adoption of IoT devices and applications, 5G networks have the potential to reshape industries, drive innovation, and enhance the quality of life for billions of people around the world. 5G communication networks represent a paradigm shift in the way we connect and communicate. With their advanced architecture, dynamic management capabilities, and transformative potential, 5G networks are poised to unlock new opportunities, accelerate digital transformation, and usher in a new era of connectivity and innovation.

Environmental sensing is a pivotal technology that utilizes sensor data to enable vehicles, robots, and drones to accurately perceive their surroundings. The emergence of 5G New Radio (NR) networks as specialized sensors for environmental sensing has become a promising research direction, particularly within the context of integrated sensing and communication (ISAC) systems. One category of ISAC research in 5G NR primarily focus on radar signal modeling to create range-Doppler imaging maps. However, the generation of range-Doppler maps demands a significant amount of continuous data in the time-frequency domain, which is usually unavailable in localization tasks that rely on time domain data. This paper focuses on utilizing the downlink pilots in 5G NR without modifying the existing communication functions, aiming to propose an implementation algorithm for sensing from the perspective of the channel model. Firstly, we investigate the performance of an inverse discrete Fourier transform (IDFT)-based channel impulse response (CIR) ranging scheme. Secondly, a CIR-based back projection (BP) algorithm for sensing is proposed, which exploits the downlink pilots of 5G NR. In this algorithm, the transceiver pair consisting of a gNB and user equipment (UE) is treated as a subaperture, and the subapertures from all gNBs are combined to emulate the effect of a synthetic aperture. Finally, the performance of the CIR-based BP sensing algorithm is demonstrated through simulations. Notably, the advantage of the proposed method is that it does not require redesigning 5G NR signals, does not interfere with communication functions, and only requires the pilot from a single orthogonal frequency division multiplexing (OFDM) symbol for sensing, thereby offering an innovative approach to environmental sensing and localization.

With the introduction of Reduced Capability (RedCap) and enhanced Reduced Capability (eRedCap) user equipment, 3GPP Release 17 and 18 define new device categories aimed at bridging the gap between traditional 5G New Radio (NR) devices and IoT-oriented solutions such as NB-IoT and eMTC. These categories target mid-tier applications, such as process / asset monitoring and electricity distribution automation, which demand reduced device complexity, high energy efficiency, and moderate data rates. In this paper, we present a comprehensive simulation-based performance analysis of 5G RedCap and eRedCap using an extended ns-3 5G-LENA implementation. Our simulation framework integrates an energy consumption model and Bandwidth Part-aware scheduling, calibrated with empirical energy measurements from commercial RedCap devices, ensuring realistic and reproducible simulation results. While eRedCap shows improved energy efficiency due to its reduced 5MHz bandwidth, its overall battery lifetime and latency tend to be inferior in practical scenarios. Our analysis proposes optimized eDRX power consumption and Release Assistance Indication (RAI) for (e)RedCap to reflect future energy-saving potential. Our results highlight both the limitations and opportunities of (e)RedCap in expanding the 5G ecosystem towards 6G.