Indoor environments present significant challenges for wireless connectivity. Public Mobile Network Operators (MNOs) utilizing outdoor macro base stations (BSs) to serve indoor customers suffer from poor signal penetration while indoor Wi-Fi networks may face reliability issues due to spectrum contention. Shared spectrum models, particularly the Citizens Broadband Radio Service (CBRS) band utilized by private 4G/5G networks, have emerged as a promising alternative to providing reliable indoor service. Moreover, these private networks are equipped with the neutral-host (NH) model, seamlessly offloading indoor MNOs’ traffic to the private CBRS network. This paper presents a comprehensive, real-world performance evaluation of three co-located technologies utilizing mid-band spectrum (1–6 GHz): a CBRS-based NH network, public MNO macro net-works, and a Wi-Fi 6 network, inside a large, big-box retail store characterized by significant building loss. While the evaluation is site-specific, it is a real-world representation of a highly dense class of indoor deployments. Our analysis demonstrates: (i) the NH network provides superior indoor coverage compared to MNO macro, requiring only six CBRS devices (CBSDs) versus 65 Access Points (APs) for enterprise Wi-Fi to achieve full coverage, with a median building loss of 26.6 dB ensuring interference-free coexistence with outdoor federal incumbents; (ii) the NH network achieves substantial indoor throughput gains, with per-channel normalized throughput improvements of 1.44× and 1.62× in downlink (DL), and 4.33× and 13× in uplink (UL), compared to 4G and 5G macro deployments, respectively; (iii) the NH deployment achieves a median indoor aggregated physical (PHY)-layer DL throughput gain of 2.08× over 5G macro deployments indoors, despite utilizing only 40 MHz of aggregated bandwidth compared to 225 MHz for 5G macro; and (iv) the NH deployment also outperforms Wi-Fi in application-layer HTTP DL performance by 5.05×. The findings offer critical insights by presenting: (i) a framework to leverage real-world deployments as testbeds for studying indoor shared-spectrum networks; and (ii) measurement-based evidence supporting the use of NH to improve indoor cellular coverage.

Indoor wireless connectivity remains a complex challenge, particularly in dense environments and underground facilities. Although modern Wi-Fi technologies (such as Wi-Fi 6, Wi-Fi 7, and future iterations) offer higher throughput, they are constrained by the limitations of unlicensed spectrum, client-driven connection decisions, and channel management complexities that make it difficult to ensure consistent Quality of Service (QoS). Mobile Network Operator (MNO) signals—especially those using mid- and high-band 5G frequencies—face significant attenuation through walls and other building materials, resulting in weak or inconsistent indoor coverage.An MNO-based Distributed Antenna System (DAS) can extend outdoor cellular coverage indoors by amplifying and redistributing the MNO’s signal; however, its performance remains limited by the capacity and bandwidth of the external MNO network. In contrast, a Neutral Host (NH) system operating in the Citizens Broadband Radio Service (CBRS) spectrum allows multiple MNOs to share a single private cellular infrastructure. This approach reduces deployment costs while enhancing coverage and capacity across enterprise and public spaces. This paper evaluates and compares four primary indoor connectivity solutions—MNO, Wi-Fi, Neutral Host (NH), and Distributed Antenna System (DAS)—by analyzing key performance indicators, including signal strength (RSRP, RSSI), Signal-to-interference ratio plus noise (SINR), and throughput. The results highlight the strengths and limitations of each technology, offering guidance on their optimal use across various indoor deployment scenarios.

Channel sounding is crucial for achieving Extremely High Throughput (EHT) and Ultra-high reliability (UHR) in next-generation Wi-Fi systems, i.e., Wi-Fi 7 and beyond. In Downlink Multi-User Multiple-Input Multiple-Output (DL MUMIMO) communications, data rate significantly deteriorates under time-varying channel with Doppler effect. Therefore, effective channel sounding mechanisms must balance the Channel State Information (CSI) overhead and CSI staleness, which is governed by the channel coherence time. Despite its critical importance, channel sounding optimization under time-varying channel conditions remains under-explored. This paper addresses this research gap by proposing a cross-layer optimization problem for the channel sounding period with the objective of maximizing data rate by considering the CSI overhead over the MAC layer and the channel capacity degradation over the PHY layer. This problem is then converted into an equivalent formulation leveraging the EHT sounding protocol, which can be solved efficiently using our proposed optimal search algorithm. Through simulations, we evaluate the baseline EHT sounding using outdated beamforming matrices and benchmark it against our proposed solution. The numerical results demonstrate that the channel sounding period optimization significantly reduces CSI overhead by up to 11% while boosting the average data rate by up to 8%.

Next-generation Wi-Fi 8 (IEEE 802.11bn) targets ultra-high reliability (UHR) by introducing coordinated beamforming (CoBF). In dense networks with multiple access points (APs), simultaneous downlink (DL) multi-user MIMO (MU-MIMO) transmissions from multiple APs can cause severe intra-basic service set (intra-BSS) and inter-BSS interference. CoBF aided by only partial channel state information (CSI) feedback through medium access control (MAC) layer frame exchange is envisioned to support concurrent DL transmission with mitigated physical-(PHY-)layer interference. To improve the network throughput, not only the interference mitigation algorithm design requires careful design but also the selection of optimal AP CoBF clusters is crucial for dense AP deployments. This paper presents a cross-layer solution combining PHY and MAC layer design to optimize AP cluster formation for Wi-Fi 8 CoBF. At the PHY layer, we introduce two beamforming nulling strategies: full nulling, which completely cancels all intra-BSS and inter-BSS interference when sufficient spatial degrees of freedom are available, and partial nulling, which is used under limited degrees of freedom to reduce interference as much as possible. Based on this, we formulate the cross-layer problem that aims to optimize the network throughput, to which we propose an exact linear programming (LP) optimization to determine the optimal AP cluster formation. A greedy clustering algorithm is proposed as a low-complexity alternate. Simulation results demonstrate that the proposed CoBF approach significantly mitigates interference and achieves substantial throughput gains in dense AP scenarios. Furthermore, the LP-optimized AP clustering yields the higher network throughput than the greedy heuristic and mixed integer linear programming (MILP) by up to 12% and 26%, highlighting the benefits of global optimization in terms of performance and time complexity.

Ensuring robust wireless coverage in a refinery's outdoor facilities poses a significant challenge due to the metal and pipe-heavy environment hindering wireless signal transmission. The difficulty arises from the need for numerous Wi-Fi Access Points (APs) to cover the expansive facility and the associated installation costs, switches, and cabling infrastructure. Traditional Wi-Fi deployment is further complicated by the unlicensed spectrum, leading to contention and collisions that impact the reliability of mission-critical applications on the network. While public cellular networks are an alternative, their limited proximity to refinery regions creates challenges. However, these Mobile Network Operator (MNO) deployments are often far from the refinery, and the base stations struggle to penetrate (if the frequency is not in low and mid-band) the metal pipes, resulting in unreliable network connections and frequent application disruptions. Our work addresses the challenge of complex environments by deploying a private network using the 3.5 to 3.7 GHz CBRS spectrum within the refinery. We proposed an optimal placement model and validated it with actual measurements. The deployed private network ensures a strong RSRP signal inside metal pipes, allowing employees to move freely and maintain seamless connectivity for their daily activities.

Wi-Fi has been widely used in commercial facilities for wireless connectivity. However, the evolving network traffic and performance requirements, especially for mission-critical applications demanding millisecond-level latency, have highlighted limitations in Wi-Fi’s traditional channel access protocol, Carrier Sense Multiple Access (CSMA), and the challenges of unlicensed spectrum. These issues result in decreased reliability and connectivity disruptions for critical applications. Moreover, seamless roaming and mobility are typically challenging in Wi-Fi networks. The introduction of private networks using Fourth Generation Long-Term Evolution (4G LTE) and Fifth Generation New Radio (5G NR) protocols has enhanced application reliability through scheduled access and interference-free spectrum usage. These deployments can be tailored for both outdoor and indoor environments. This study examines actual field deployments and their test results in environments like oil refineries, warehouses, outdoor parking areas, and distribution centers. We compare actual measurements with a theoretical model to validate the performance enhancements and understand the practical implications for real-world applications. We analyzed performance factors such as signal strength (Reference Signal Received Power (RSRP) heat maps), coverage, packet latency, and mobility. This research provides insights into the practical performance of private networks and their suitability for supporting mission-critical applications in diverse settings.

The emergence of the Internet of Things (IoT) has triggered a massive digital transformation across numerous sectors. This transformation requires efficient wireless communication and connectivity, which depend on the optimal utilization of the available spectrum resource. Given the limited availability of spectrum resources, spectrum sharing has emerged as a favored solution to empower IoT deployment and connectivity, so adequate planning of the spectrum resource utilization is thus essential to pave the way for the next generation of IoT applications, including 5G and beyond. This article presents a comprehensive study of prevalent wireless technologies employed in the field of the spectrum, with a primary focus on spectrum-sharing solutions, including shared spectrum. It highlights the associated security and privacy concerns when the IoT devices access the shared spectrum. This survey examines the benefits and drawbacks of various spectrum-sharing technologies and their solutions for various IoT applications. Lastly, it identifies future IoT obstacles and suggests potential research directions to address them.

IEEE 802.11be (Wi-Fi 7) introduces a new concept called multi-link operation (MLO), which allows multiple Wi-Fi interfaces in different bands (2.4, 5, and 6 GHz) to work together to increase network throughput, reduce latency, and improve spectrum reuse efficiency in dense overlapping networks. To make the most of MLO, this paper proposes a new data-driven resource allocation algorithm for the 11be network with the aid of an access point (AP) controller. To maximize network throughput, a network topology optimization problem is formulated for 11be network, which is solved by exploiting the totally unimodular property of the bipartite graph formed by the connection between AP and station (STA) in Wi-Fi networks. Subsequently, a proportional fairness algorithm is applied for radio link allocation, network throughput optimization considering the channel condition, and the fairness of the multi-link device (MLD) data rate. The performance of the proposed algorithm on two main MLO implementations -multi-link multi-radio (MLMR) with simultaneous transmission and reception (STR), and the interplay between multiple nodes employing them are evaluated through cross-layer (PHY-MAC) data rate simulation with PHY abstraction.

The 3.7 - 3.98 GHz frequency band (also known as C-band) was recently allocated in the US for the deployment of 5G cellular services. Prior to this, the lower adjacent band, 3.55 - 3.7 GHz, had been allocated to Citizens Broadband Radio Service (CBRS), where the entire 150 MHz can be used for free by Tier 3 General Authorized Access (GAA) users, under strict authorization of the Spectrum Access System (SAS). However, adjacent channel interference may reduce the performance of GAA and C-band systems due to lack of guard bands and no Time Division Duplexing (TDD) synchronization, i.e., uplink/downlink configurations are not synchronized. In this paper, we quantify the effect of this mutual interference by performing experiments with a real-world deployment. Significant downlink throughput reductions on both systems are observed when two devices are in close proximity to each other, with one is transmitting uplink while the other is transmitting downlink: 60% for 4G CBRS and 43% for 5G C-band. We believe that this is the first paper to demonstrate this in a real deployment. This throughput degradation was reduced when the CBRS base-station (i.e., CBSD) changed its channel and operated 20 MHz away from C-band, essentially creating a guard band between the channels. We also demonstrate the improvement in latency under adjacent channel interference by implementing MicroSlicing at the CBSD. Our results indicate that addressing adjacent channel interference due to the lack of guard bands and TDD configuration mismatch is crucial to improving the performance of both CBRS and C-band systems.

5G-NR is beginning to be widely deployed in the mmWave frequencies in urban areas in the US and around the world. Due to the directional nature of mmWave signal propagation, improving performance of such deployments heavily relies on beam management and deployment configurations. We perform detailed measurements of mmWave 5G deployments by two major commercial 5G operators in the US in two diverse environments: an open field with a baseball park (BP) and a downtown urban canyon region (DT), using smartphone-based tools that collect detailed measurements across several layers (PHY, MAC and up) such as beam-specific metrics like signal strength, beam switch times, and throughput per beam. Our measurement analysis shows that the parameters of the two deployments differ in a number of aspects: number of beams used, number of channels aggregated, and density of deployments, which reflect on the throughput performance. Our measurement-driven propagation analysis demonstrates that narrower beams experience a lower path-loss exponent than wider beams, which combined with up to eight frequency channels aggregated on up to eight beams can deliver a peak throughput of 1.2 Gbps at distances greater than 100m.

In this study, we present the first measurement study of commercial IEEE 802.11 Wi-Fi wireless local-area network (WLAN) and 3GPP 5G LAN (i.e., CBRS) networks in terms of latency, packet drop, and throughput. As the number of downlink and uplink traffic increases in the WLAN network, we observed significant number of packet drops and increased latency on the delay sensitive traffic, especially in mobility test cases where mobile devices roam from one Access Point (AP) to another AP. On the other hand, in both static and mobility test cases, packet drop rate of 5G LAN is consistently low at the desired target level due to interference free spectrum channel and efficient allocation of radio resources at MAC scheduling. Also, in the 5G LAN network, the Celona Micro-slicing feature guarantees minimum latency in a consistent manner across different test conditions. During the capacity experiments, we observed that, as the load increases, 5G LAN is able to guarantee fair allocation of radio resource among the connected users compared to WLAN system. In the end, we ran test with realistic enterprise use-case applications such as Zoom, Bar-code scanning, VOIP, and Camera to observe and analyze the user experience in WLAN and 5G LAN systems.

To meet the rising data-offloading demands, IEEE 802.11-based WiFi networks have undergone consistent densification. The unlicensed spectrum has also been harnessed through LTE-WiFi coexistence. However, in dense and ultradense networks (DNs/UDNs), the network capacity is even more adversely impacted by the endemic interference. Yet, the precise nature of Capacity Interference Relationship (CIR) in DNs/UDNs and LTE-WiFi coexistence remains to be studied. Densification also exacerbates the challenges to network optimization. The conventional approaches to simplify the complex SINR-Capacity constraints lead to high convergence times in DN/UDN optimization. We investigate the CIR in dense and ultra-dense WiFi (IEEE 802. 11a) and LTE-WiFi (LTULAA) networks through real-time experiments. We then subject the empirical data to linear and polynomial regression to determine the nature of CIR and demonstrate that strong linear correlations may exist. We also study the impact of predictor variables, topology, and radio access technology on CIR. Most importantly, we propose CIRNO, a CIR-inspired network optimization approach, wherein the empirically determined CIR equation replaces the theoretically assumed SINR-Capacity constraints in optimization formulations. We evaluate CIRNO by implementing three recent works on optimization. We demonstrate the relevance of CIR and CIRNO in DNs/UDNs through a significant reduction in convergence times (by over 50%) while maintaining high accuracy (over 95%). To the best of our knowledge, this is the first work to statistically analyze CIR in DNs/UDNs and LTE-WiFi heterogeneous networks (HetNets) and to use CIR regression equations in network optimization.

LTE-U (LTE-Unlicensed) is designed to coexist with Wi-Fi in the unlicensed band by balancing its duty cycle according to the number of coexisting Wi-Fi access points (APs) it detects. For example, a LTE-U base-station (BS) will reduce its duty cycle from 50% to 33% when it senses an increase in the number of co-channel Wi-Fi basic service sets (BSSs) from one to two. But the problem of detecting how many WiFi BSS' are operating on the channel in real-time, without decoding the Wi-Fi header, still remains. In this paper, we present a novel algorithm that solves the problem by using an autocorrelation (AC) function on the Wi-Fi preamble and setting appropriate detection thresholds to infer the number of Wi-Fi BSSs operating on the channel. Performing auto-correlation on the Wi-Fi preamble is a much simpler operation than decoding the entire Wi-Fi packet, which is what would be needed if one were to decode the MAC header to identify the BSS. We implement and experimentally validate the proposed AC detector and demonstrate that there is a differentiable pattern of AC events between one and two Wi-Fi APs. From the collected AC events, we determine a suitable threshold for a reliable detection of Wi-Fi APs. We show that using an AC threshold of NE= 0.8, we can achieve a probability of detection (PD) of 0.9 with a probability of false alarm (PFA) of less than 0.02. Finally, we demonstrate that the performance of the proposed AC detector is superior in terms of PDand PFA compared with the energy detector (ED).

In this paper, we develop an algorithm, based only on energy detection, to detect the number of Wi-Fi basic service sets (BSSs) operating on the same channel. Such an algorithm can be used by a LTE-U base station (BS) to scale back its duty cycle when coexisting with Wi-Fi on the same channel. According to the LTE-U specification, a LTE-U BS scales back its duty cycle from 50% to 33% when it senses that the number of co-channel Wi-Fi BSSs has increased from one to two. There are two ways that this detection can be done: (a) decoding based, where the LTE-U BS decodes the Wi-Fi packet header to determine the unique Wi-Fi basic service set identification (BSSID) and (b) energy based, where only received energy levels are used to determine the number of Wi-Fi BSSs. The former approach requires an LTE-U BS to implement a Wi-Fi decoder and hence increases complexity, whereas the latter is easier to implement, requiring only an energy detector and appropriate detection thresholds to distinguish between one and two Wi-Fi APs. We analyze the latter approach and experimentally verify the feasibility of an energy detector to reliably distinguish between one and two Wi-Fi APs. In order to do so, we first experimentally determine appropriate detection thresholds using comprehensive measurements in realistic environments, both line-of-sight (LOS) and non-LOS (NLOS). These thresholds are then used to perform hypothesis based detection to devise an efficient algorithm that predicts presence of one or two Wi-Fi BSSs. The performance of the proposed algorithm is evaluated, both theoretically and experimentally, by utilizing two metrics (a) probability of detection ($P_D$) and (b) probability of false alarm ($P_{FA}$). We show that using a threshold of -42 dBm delivers greater than 80% $P_D$ and less the 5% $P_{FA}$ which we verify both theoretically and experimentally. Hence energy based detection is a low-complexity means of determining number of Wi-Fi BSSs to help LTE-U scale back its duty cycle appropriately.

A multitude of Channel Assignment (CA) schemes have created a paradox of plenty, making CA selection for Wireless Mesh Networks (WMNs) an onerous task. CA performance prediction (CAPP) metrics are novel tools that address the problem of appropriate CA selection. However, most CAPP metrics depend upon a variety of factors such as the WMN topology, the type of CA scheme, and connectedness of the underlying graph. In this work, we propose an improved Channel Assignment Link-Weight Metric (iCALM) that is independent of these constraints. To the best of our knowledge, iCALM is the first universal CAPP metric for WMNs. To evaluate iCALM, we design two WMN topologies that conform to the attributes of real-world mesh network deployments, and run rigorous simulations in ns-3. We compare iCALM to four existing CAPP metrics, and demonstrate that it performs exceedingly well, regardless of the CA type, and the WMN layout.

In this paper we address the issue of association fairness when Wi-Fi and LTE unlicensed (LTE-U) coexist on the same channel in the unlicensed 5 GHz band. Since beacon transmission is the first step in starting the association process in Wi-Fi, we define association fairness as how fair LTE-U is in allowing Wi-Fi to start transmitting beacons on a channel that it occupies with a very large duty cycle. According to the LTE-U specification, if a LTE-U base station determines that a channel is vacant, it can transmit for up to 20 ms and turn OFF for only 1 ms, resulting in a duty cycle of 95%. In an area with heavy spectrum usage, there will be cases when a Wi-Fi access point wishes to share the same channel, as it does today with Wi-Fi. We study, both theoretically and experimentally, the effect that such a large LTE-U duty cycle can have on the association process, specifically Wi-Fi beacon transmission and reception. We demonstrate via an experimental set-up using National Instrument (NI) USRPs that a significant percentage of Wi-Fi beacons will either not be transmitted in a timely fashion or will not be received at the LTE-U BS thus making it difficult for the LTE-U BS to adapt its duty cycle in response to the Wi-Fi usage. Our experimental results corroborate our theoretical analysis. We compare the results with Wi-Fi/Wi-Fi coexistence and demonstrate that LTE-U/Wi-Fi coexistence is not fair when it comes to initial association since there is a much larger percentage of beacon errors in the latter case. Hence, the results in the paper indicate that in order to maintain association fairness, a LTE-U BS should not transmit at such high duty cycles, even if it deems the channel to be vacant.

Cellular Internet of Things (C-IoT) is one of the emerging 5G technologies. 4G LTE being the most promising cellular technology so far and is a suitor for serving C-IoT devices. In future millions of C-IoT devices will be deployed in the coverage of a single 4G LTE base station. However, the existing random access (RACH) mechanism in 4G LTE is not designed to connect millions of devices. Hence, in this paper, we propose a novel RACH mechanism that allows millions of C-IoT devices to associate with the base station within the existing 4G LTE framework. 3GPP has proposed an extended access barring mechanism to solve this problem for machine type communication (MTC). We compare the performance of the proposed RACH mechanism with the existing 3GPP extended access barring mechanism through analysis. Further, through simulation results, we show that the proposed mechanism is faster and saves power when compared to existing 3GPP extended access barring mechanism under perfect synchronization.

Cellular heterogeneous networks (HetNets) are going to be one of the key enablers for 5G. Downlink/Uplink decoupling (DUDe) is a concept in which a mobile device is connected with Macro cell for downlink communication and with small cell for uplink communication in LTE/LTE-A HetNets. It improves uplink data rate, reduces power consumption of devices, balances load between Macro cell and small cells. Due to incorporation of DUDe, a mobile device has to perform separate uplink and downlink handovers unlike traditional handovers in coupled LTE networks. In this paper, we propose various handover schemes for DUDe LTE networks. Apart from this, we have mathematically analysed the received SINR by small cells taken part in decoupling, with respect to a device moving in decoupling regions of these small cells, in multiple cell interference scenario. Simulation results show the signaling impact of DUDe in handovers, increased uplink SINR, decreased power consumption of devices in both single small cell and multiple small cell scenarios.

Femto cells a.k.a. Low Power Nodes (LPNs) are used to improve indoor data rates as well as to reduce traffic load on macro Base Stations (BSs) in LTE cellular networks. These LPNs are deployed inside office buildings and residential apartment complexes to provide high data rates to indoor Users. With high SINR (Signal-to-Interference plus Noise Ratio) the users experience good throughput, but the SINR decreases significantly because of interference and obstacles such as building walls, present in the communication path. So, efficient placement of Femtos in buildings while considering Macro-Femto interference is very crucial for attaining desirable SINR. At the same time, minimizing the power leakage in order to improve the signal strength of outdoor users in a high interference (HIZone) around the building area is important. In our work, we have considered obstacles (walls, floors) and interference between Macro and Femto BSs. To be fair to both indoor and outdoor users, we designed an efficient placement and power control SON (Self organizing Network) algorithm which optimally places Femtos and dynamically adjusts the transmission power of Femtos based on the occupancy of Macro users in the HIZone. To do this, we solve two Mixed Integer Programming (MIP) methods namely: Minimize number of Femtos (MinNF) method which guarantees threshold SINR (SINRTh) -2dB for all indoor users and optimal Femto power (OptFP) allocation method which guarantees SINRTh(- 4 dB) for indoor users with the Macro users SINR degradation as lesser than 2dB.

Femto cells have been integrated into 4G Long Term Evolution (LTE) cellular network architecture to efficiently address the coverage and capacity issues faced in indoors and at hotspots. Though spectral efficiency increases through frequency reuse one at Femtos, it could lead to co-tier interference and cause higher interference for cell edge User Equipments (UEs). This problem is more severe in enterprise and hotspot Femto deployments due to dense placement of Femtos. Existing co-tier interference management techniques do not solve this problem completely. Hence, in this paper, we propose a Variable Radius (VR) algorithm which dynamically increases or decreases the cell edge/non-cell edge region of Femtos and efficiently allocates the radio resources among cell edge/non-cell edge region of Femtos so that the co-tier interference between neighboring Femtos can be avoided. We implemented the proposed VR algorithm on top of Proportional Fair (PF) scheduling algorithm in NS-3 simulator. In our experiments, for 90 UEs the proposed technique (VR + PF) achieved 29% and 38% improvement in average throughput for static and mobile scenarios, respectively when compared to classic PF algorithm without any interference management.