Ubiquitous connectivity is essential for emerging edge-assisted machine-type communication (MTC) applications for net-worked robotics, intelligent transportation, smart surveillance, etc., which demand ultra-low latency, high data rate, reliability, and energy efficiency. These applications generate significant uplink traffic, often consisting of raw sensor data, where the utility of data is closely tied to its timeliness. The traffic patterns in these scenarios are event-driven, characterized by high variability and bursts, making them difficult to predict. While 5G networks provide Radio Resource Control (RRC) states-Idle, Inactive, and Connected-designed to manage latency and user equipment (UE) power consumption based on deterministic traffic patterns like video streaming, they may not be optimized for the unpredictable nature of MTC traffic. In this study, we evaluate the performance of legacy 5G systems in handling MTC traffic using the open-source 3GPP-compliant testbed, Open Air Interface (OAI). Our analysis reveals that current 5G UE connection setup mechanisms can adversely affect control latency and UE power consumption due to the irregular and event-driven nature of MTC traffic. To mitigate these issues, we propose an enhanced connection setup process that allows UEs to remain in idle mode during inactivity, thereby conserving power, and facilitating a rapid transition to connected mode with reduced signaling overhead and power consumption. We implement and validate this framework on the OAI testbed, demonstrating its compatibility with the 3GPP standard. Empirical results indicate that our proposed method can reduce UE control latency and power consumption by up to$4\times$and$3\times$respectively, compared to legacy 5G connection setup approaches.

Global allocations in the upper mid-band spectrum (4-24 GHz) necessitate a comprehensive exploration of the propagation behavior to meet the promise of coverage and capacity. This paper presents an extensive Urban Microcell (UMi) outdoor propagation measurement campaign at 6.75 GHz and 16.95 GHz conducted in Downtown Brooklyn, USA, using a 1 GHz bandwidth sliding correlation channel sounder over 40-880 m propagation distance, encompassing seven Line of Sight (LOS) and 13 Non-Line of Sight (NLOS) locations. Analysis of the path loss (PL) reveals lower directional and omnidirectional PL exponents compared to mmWave and sub-THz frequencies in the UMi environment, using the close-in (CI) free space PL (FSPL) model with a 1 m reference distance. Additionally, a decreasing trend in root mean square (RMS) delay spread (DS) and angular spread (AS) with increasing frequency was observed. The measured NLOS RMS DS and RMS AS mean values (as computed by 3GPP methods) are found to be consistently lower compared to 3GPP model predictions. Point-data tables with corresponding site-specific environmental information for all measured statistics at each TX-RX location are provided to support the models and results. The spatio-temporal statistics presented here offer valuable insights for the design of nextgeneration wireless systems and networks.

This paper presents detailed radio propagation measurements for an indoor factory (InF) environment at$\mathbf{6. 7 5 ~ G H z}$and 16.95 GHz using a 1 GHz bandwidth channel sounder. Conducted at the NYU MakerSpace in the NYU Tandon School of Engineering campus in Brooklyn, NY, USA, our measurement campaign characterizes the radio propagation in a representative small factory with diverse machinery and open workspaces across 12 locations, comprising five line-of-sight (LOS) and seven non-line-of-sight (NLOS) scenarios. Analysis using the close-in (CI) free space path loss (FSPL) model with a 1 m reference distance reveals path loss exponents (PLE) below 2 in LOS at 6.75 GHz and 16.95 GHz, while in NLOS, PLE is similar to free-space propagation (e.g., PLE = 2). The RMS delay spread (DS) decreases at higher frequencies with a clear frequency dependence. Also, measurements show a wider RMS angular spread (AS) in NLOS compared to LOS at both frequency bands, with a decreasing trend as frequency increases. These observations in a densescatterer factory environment demonstrate frequency-dependent behavior that differs from existing industry-standard 3GPP models. Our findings provide crucial insights into complex propagation mechanisms in factory environments, essential for designing robust air interface and industrial wireless networks at the upper mid-band FR3 spectrum.

This paper presents a thorough validation of the Third Generation Partnership Project (3GPP) Technical Report (TR) 38.901 indoor hotspot (InH) path loss model, as part of the 3GPP Release 19 study on “Channel model validation of TR 38.901 for 7-24 GHz,” for 6G standardization. Specifically, we validate the 3GPP TR 38.901 path loss model for the InH scenario in both line of sight (LOS) and non line of sight (NLOS) channel conditions, using the floating intercept (FI) and alpha-beta-gamma (ABG) path loss models. The validation focuses on specific frequencies, including 6.75 GHz and 16.95 GHz, as well as the broader 7-24 GHz and 0.5-100 GHz frequency ranges. The validation is based on real-world measurements conducted at 6.75 GHz, 16.95 GHz, 28 GHz, and 73 GHz by NYU WIRELESS using a 1 GHz wideband time domain based sliding correlation channel sounder in the InH scenario for both LOS and NLOS channel conditions. Our results confirm that the 3GPP TR 38.901 path loss model for the InH scenario remains valid for the 7-24 GHz range in both LOS and NLOS conditions and provide valuable input for 6G standardization efforts.

New spectrum allocations in the 4–8 GHz FR1(C) and 7–24 GHz FR3 mid-band frequency spectrum are being considered for 5G/6G cellular deployments. This paper presents results from the world’s first comprehensive indoor hotspot (InH) propagation measurement campaign at 6.75 GHz and 16.95 GHz in the NYU WIRELESS Research Center using a 1 GHz wideband channel sounder system over distances from 11 to 97 m in line-of-sight (LOS) and non-LOS (NLOS). Analysis of directional and omnidirectional path loss (PL) using the close-in free space 1 m reference distance model shows a familiar waveguiding effect in LOS with an omnidirectional path loss exponent (PLE) of 1.40 at 6.75 GHz and 1.32 at 16.95 GHz. Compared to mmWave frequencies, the directional NLOS PLEs are lower at FR3 and FR1(C), while omnidirectional NLOS PLEs are similar, suggesting better propagation distances at lower frequencies for links with omnidirectional antennas at both ends of the links, but also, importantly, showing that higher gain antennas will offer better coverage at higher frequencies when antenna apertures are kept same over all frequencies. Comparison of the omnidirectional and directional RMS delay spread (DS) at FR1(C) and FR3 with mmWave frequencies indicates a clear decrease with increasing frequency. The mean spatial lobe and omnidirectional RMS angular spread (AS) is found to be wider at 6.75 GHz compared to 16.95 GHz indicating more multipath components are found in the azimuthal spatial domain at lower frequencies.

The 4-8 GHz FR1(C) and 7-24 GHz upper mid-band FR3 spectrum are promising new 6G spectrum allocations being considered by the International Telecommunications Union (ITU) and major governments around the world. There is an urgent need to understand the propagation behavior and radio coverage, outage, and material penetration for the global mobile wireless industry in both indoor and outdoor environments in these emerging frequency bands. This work presents measurements and models that describe the penetration loss in co-polarized and cross-polarized antenna configurations, exhibited by common materials found inside buildings and on building perimeters, including concrete, low-emissivity glass, wood, doors, drywall, and whiteboard at 6.75 GHz and 16.95 GHz. Measurement results show consistent lower penetration loss at 6.75 GHz compared to 16.95 GHz for all ten materials measured for co and cross-polarized antennas at incidence. For instance, the low-emissivity glass wall presents 33.7 dB loss at 6.75 GHz, while presenting 42.3 dB loss at 16.95 GHz. Penetration loss at these frequencies is contrasted with measurements at sub-6 GHz, mmWave and sub-THz frequencies along with 3GPP material penetration loss models. The results provide critical knowledge for future 5G and 6G cellular system deployments as well as refinements for the 3GPP material penetration models.

The next generation of wireless communication is expected to harness the potential of the sub- THz bands to achieve exceptional performance and ubiquitous connectivity. However, network simulators such as ns-3 currently lack support for channel models above 100 GHz. This limits the ability of researchers to study, design, and evaluate systems operating above 100 GHz. Here, we use the drop-based NYUSIM channel model to simulate channels above 100 GHz in all 3GPP scenarios including urban microcell (UMi), urban macrocell (UMa), rural macrocell (RMa), indoor hotspot (InH), and indoor factory (InF). We evaluate the full stack downlink end-to-end performance (throughput, latency, and packet drop) experienced by a single user equipment (UE) connected to a Next Generation Node B (gNB) operating in the sub- THz bands for three gNB-UE antenna configurations: 8x8-4x4, 16xI6-4x4, and 64x64-8x8 by using the NYUSIM channel model at 140 GHz in the ns-3 mmWave module. Our simulations demonstrate that sub-THz bands can enable high-fidelity applications that require data rates exceeding 1 Gbps and latency below 15 milliseconds (ms) using the current mmWave protocol stack, and large antenna arrays. In addition, we show the variation in throughput vs number of realizations and find the optimal number of realizations required to obtain statistically significant results. We strongly encourage researchers worldwide to adopt a similar approach, as it enables the readers to assess the accuracy and reliability of the reported results and enhance the findings” overall interpretability.

This paper presents sub-Terahertz (THz) channel characterization and modeling for an indoor industrial scenario based on radio propagation measurements at 142 GHz in four factories. We selected 82 transmitter-receiver (TX-RX) locations in both line-of-sight (LOS) and non-LOS (NLOS) conditions and collected over 75,000 spatial and temporal channel impulse responses. The TX-RX distance ranged from 5 to 87 m. Steerable directional horn antennas were employed at both ends and were switched between vertical and horizontal polarization. Measurements were conducted with the low RX and high RX to characterize the propagation channel for close-to-floor applications such as automated guided vehicles. Results show that the low RXs experience an average path loss increase of 10.7 dB and 6.0 dB at LOS and NLOS locations, respectively. In addition, channel enhancement measurements were conducted using a steerable large flat metal plate as a passive reflecting surface, demonstrating omnidirectional path loss reduction from 0.5 to 22 dB with a mean of 6.5 dB. This paper presents the first statistical channel characterization and path loss modeling at sub-THz frequencies, highlighting the potential for ultra-broadband factory communications in the 6G era.

Radio channels at mmWave and sub-THz frequencies for 5G and 6G communications offer large channel band-widths (hundreds of MHz to several GHz) to achieve multi-Gbps data rates. Accurate modeling of the radio channel for these wide bandwidths requires capturing the absolute timing of multipath component (MPC) propagation delays with sub-nanosecond accuracy. Achieving such timing accuracy is challenging due to clock drift in untethered transmitter (TX) and receiver (RX) clocks used in time-domain channel sounders, yet will become vital in many future 6G applications. This paper proposes a novel solution utilizing precision time protocol (PTP) and periodic drift correction to achieve absolute timing for MPCs in power delay profiles (PDPs) -captured as discrete samples using sliding correlation channel sounders. Two RaspberryPi computers are programmed to implement PTP over a dedicated Wi-Fi link and synchronize the TX and RX Rubidium clocks continuously every second. This synchronization minimizes clock drift, reducing PDP sample drift to 150 samples/hour, compared to several thousand samples/hour without synchronization. Additionally, a periodic drift correction algorithm is applied to eliminate PDP sample drift and achieve sub-nanosecond timing accuracy for MPC delays. The achieved synchronicity eliminates the need for tedious and sometimes inaccurate ray tracing to synthesize omnidirectional PDPs from directional measurements. The presented solution shows promise in myriad applications, including precise position location and distributed systems that require sub-nanosecond timing accuracy and synchronization among components.

In this paper, we expand upon a new metric called the Waste Factor$(W)$, a mathematical framework used to evaluate power efficiency in cascaded communication systems, by accounting for power wasted in individual components along a cascade. We show that the derivation of the Waste Factor, a unifying metric for defining wasted power along the signal path of any cascade, is similar to the mathematical approach used by H. Friis in 1944 to develop the Noise Factor$(F)$, which has since served as a unifying metric for quantifying additive noise power in a cascade. Furthermore, the mathematical formulation of$W$can be utilized in artificial intelligence (AI) and machine learning (ML) design and control for enhanced power efficiency. We consider the power usage effectiveness (PUE), which is a widely used energy efficiency metric for data centers, to evaluate$w$for the data center as a whole. The use of$W$allows easy comparison of power efficiency between data centers and their components. Our study further explores how insertion loss of components in a cascaded communication system influences$w$at 28 GHz and 142 GHz along with the data rate performance, evaluated using the consumption efficiency factor (CEF). We observe CEF's marked sensitivity, particularly to phase shifter insertion loss changes. Notably, CEF variations are more prominent in uplink transmissions, whereas downlink transmissions offer relative CEF stability. Our exploration also covers the effects of varying User Equipment (UE) and Base Station (BS) deployment density on CEF in cellular networks. This work underscores the enhanced energy efficiency at 142 GHz, compared to 28 GHz, as UE and BS numbers escalate.

Accurate channel modeling and simulation tools are vital for studying sub-THz and millimeter (mmWave) wideband communication system performance. To accurately design future high data rate, low latency wireless modems, the entire protocol stack must be appropriately modeled to understand how the physical layer impacts the end-to-end performance experienced by the end user. This paper presents a full stack end-to-end performance analysis in ns-3 using drop-based NYU channel model (NYUSIM) and 3GPP statistical channel model (SCM) in scenarios, namely urban microcell (UMi), urban macrocell (UMa), rural macrocell (RMa), and indoor hotspot (InH) at 28 GHz with 100 MHz bandwidth. Video data is transmitted at 50 Mbps using User Datagram Protocol (UDP), and we observe that the RMa channel is benign in non-line of sight (NLOS) for NYUSIM and 3GPP SCM as it exhibits no packet drops and yields maximum throughput (48.1 Mbps) and latency of ∼ 20 ms. In NLOS, for NYUSIM, the UMa and RMa channels are similar in terms of throughput and packet drops, and the latency in UMi and InH scenarios is 10 times and 25 times higher respectively compared to UMa. Our results indicate that mmWave bands can support data rates of 50 Mbps with negligible packet drops and latency below 150 ms in all scenarios using NYUSIM.

Virtual sensor provisioning is an essential process in sensor-cloud-based Internet of Things (IoT), and it is responsible for the efficient utilization of physical resources in the system. However, the existing schemes for virtual sensor provisioning do not provide an optimal solution while considering overall demand of multiple users/services. As a result, redundant sensor nodes are provisioned, which leads to increased energy consumption and reduced network lifetime. In this paper, we present a dynamic virtual sensor provisioning scheme for sensor-cloud-based IoT applications to maintain the energy efficiency of the deployed physical sensor nodes while maintaining the quality of service (QoS) of the service requests. We model the interaction between the cloud service provider and the sensor owners using the single-leader multifollower Stackelberg game. The players of the game exploit the spatial correlation among the on-field sensor nodes, and consequently, the oligopoly created between the players is dynamically updated. We show the existence of a Stackelberg-Nash-Cournot equilibrium in the game. We evaluated the performance of the proposed scheme through extensive simulations. The results depict improvement in the energy efficiency of the nodes as well as increase in the lifetime of the deployed on-fields sensors in the proposed scheme compared to benchmark schemes. We also plot the average number of QoS violations in each iteration for the user requests.