As Open Radio Access Networks (Open RAN) move toward large-scale deployment, the industry requires a transition from binary “pass/fail” conformance testing to a rigorous performance metrology that characterizes system stability in multi-vendor environments. This study introduces a statistical factor screening methodology, utilizing a Resolution V fractional factorial design, to isolate the key configuration parameters that govern interoperability in a commercial-grade 7.2x functional split testbed. By executing a 1,024-run automated experimental campaign, we identify critical non-linear "performance boundaries" where specific combinations of modulation coding, power control, and UE scaling cause functional decoupling between disaggregated O-DU and O-RU components. Our results demonstrate that O-RU interoperability is not a static state but a dynamic boundary of functional invariance. This work provides a mathematically grounded framework for Mobile Network Operators (MNOs) to prioritize high-impact factors in certification and badging, accelerating the maturity of secure, high-capacity Open RAN ecosystems.

Efficient power allocation is crucial for mitigating intercell interference in multi-cell wireless networks. In recent years, reinforcement learning (RL) algorithms, such as Q-learning (QL), Double Q-learning (DQL), and Deep Q-Network (DQN), have been proposed for downlink power control in dynamic radio environments. In this paper, we propose a system model to simulate downlink 4G/5G intercell interference and implement Multi-Agent Deep Reinforcement Learning (MADRL) algorithms, including Multi-Agent Proximal Policy Optimization (MAPPO) and DQN with Centralized Training and Decentralized Execution (DQN-CTDE), to optimize the average cell throughput in multi-cell coexisting 4G/5G networks. In addition, we compare the effect of frequency overlap for 4G vs. 4G, 4G vs. 5G, and 5G vs. 5G systems. Due to their multi-agent framework, simulation results show that both MAPPO and DQN-CTDE outperform other traditional RL methods such as QL, DQL, and DQN. MAPPO achieves the highest average throughput, followed by DQN-CTDE. The results are useful for modeling mutual interference and selecting the most suitable multi-agent deep RL method to optimize the downlink transmit power in the 4G/5G coexistence scenarios.

We present airtime utilization measurements of the IEEE 802.11ax WLAN in the 6 GHz band in different scenarios: various numbers of access points and clients, and in MIMO and SISO configurations. The measurement setup is based on 802.11ax development boards and open-source software. We present a methodology based on physical-level measurements and compare the airtime utilization for different throughput values and bandwidths, for downlink and uplink traffic. The results show that higher bandwidths reduce airtime utilization, MIMO reduces airtime utilization by up to 36.2 %, an additional client increases airtime utilization by up to 23.9 %, and mutually interfering 802.11ax networks increase airtime utilization by up to 27.3 %. This study provides useful guidelines for researchers and policymakers in the context of wireless coexistence in the 6 GHz band and electromagnetic compatibility characterization of 802.11ax devices.

With the rapid deployment of 5G NR in the sub-6 GHz frequency bands, cellular operators need to accommodate this new technology within the limited spectrum licensed to them, occupied mainly by 4G LTE. This poses the challenge of migrating their 4G infrastructure to 5G, while supporting current 4G systems in the same band. This indicates a need for wireless coexistence between 4G and 5G systems. In this paper, we present measurements of mutual downlink interference between two adjacent 4G and 5G cells. The setup is based on software-defined radios operating with cellular open-source software. The measurements show the effect of different levels of frequency overlap, from adjacent channel to co-channel, and various levels of signal-to-interference ratio (SIR). The network performance is quantified using throughput and packet loss. The results show that higher frequency overlap and lower SIR cause lower throughput and increased packet loss and that the overlap region might affect the performance. This setup can be used to study further coexistence scenarios.

The mmWave radio frequency (RF) spectrum allocations provide a large bandwidth and an excellent dynamic spectrum sharing (DSS) opportunity for emerging 5G NewRadio unlicensed (NR-U) and Wireless Gigabit (WiGig) services. To support constructive DSS, we outline a new modeling and analytical method to jointly evaluate the effects of a multiplebeam directional listen-before-talk (MB-DLBT) protocol, intercell interferences (ICIs), and spectrum sensing errors on the NR-U and WiGig DSS system performance. Available works did not provide a systematic and analytical approach to evaluate these effects, but only relied on computer simulations. Our numerical evaluation provides an insightful observation on the performance advantage of the MB-DLBT over the single-beam DLBT and omni-directional LBT schemes. This result provides a powerful tool to support performance analysis and optimization of mmWave DSS schemes.

We present the empirical Physical Uplink Shared Channel radiated power of a User Equipment in a commercial Long-Term Evolution Frequency Division Duplex system in open-and closed-Loop power control. We present new insights, targeted on power control, from the data taken by NASCTN Report-7, which presents measured radiated PUSCH channel power, while varying 28 different system factors. The NASCTN experiment was performed to examine the impact of each of the 28 factors on the radiated emissions of LTE UEs. Here, we address how the choice of power control algorithm impacts the radiated UE emissions. We examine the results of two cases: Reference Signals Received Power equal to −78 dBm and −98 dBm. We show significant differences in UE emissions using an open- or closed-loop power control algorithm in a stable RF environment. We discuss the difference in detail and note that the UE is not precisely following the power control equation as expected in all cases. This work is performed on a commonly used UE model in North America. The results can have implications for those looking to model or control 4G LTE UE emissions and designing accurate power control algorithms for emerging cellular systems such as 5G New Radio.

In this paper, we report on a software-defined radio (SDR) based test setup to emulate and evaluate the performance of two wireless coexistence scenarios. The first case we study consists of two long-term evolution (LTE) downlink channels from adjacent cells, and the second case is formed by an LTE downlink channel coexisting with a wireless local network (WLAN) channel. Different from available SDR measurement works, this test design provides new methods such as real-time adjustment of communication and inter-cell interference (ICI) channel gains, the measurement of SDR receiver internal noise power and noise figure, and the measurement of link signal-to-interference-and-noise ratio (SINR). We compare the measured LTE SINR-to-throughput mapping result with a theoretical upper bound which assumes 3GPP reference channel quality indicator (CQI) values and an ideal communication hardware. Our measurement results illustrate the SINR gap caused by the effects of imperfect SDR hardware and noise figure, and show interesting findings about LTE and WLAN performance under varying mutual interference conditions. Our SDR design and measurement methods can be extended to support the performance evaluation and optimization of more general multicell LTE and WLAN coexistence systems.

Radio spectrum is a scarce resource. To meet demands, new wireless technologies must operate in shared spectrum over unlicensed bands (coexist). We consider coexistence of Long-Term Evolution (LTE) License-Assisted Access (LAA) with incumbent Wi-Fi systems. Our scenario consists of multiple LAA and Wi-Fi links sharing an unlicensed band; we aim to simultaneously optimize performance of both coexistence systems. To do this, we present a technique to continuously estimate the Pareto frontier of parameter sets (traces) which approximately maximize all convex combinations of network throughputs over network parameters. We use a dimensionality reduction approach known as active subspaces to determine that this near-optimal parameter set is primarily composed of two physically relevant parameters. A choice of two-dimensional subspace enables visualizations augmenting explainability and the reduced-dimension convex problem results in approximations which dominate random grid search.

The radio spectrum is becoming an increasingly scarce and valuable resource to such an extent that sharing the unlicensed bands is inevitable. In this work, we consider a multi-cell, multi-user massive multiple-input multiple-output (MIMO) coexistence scenario where multiple 5G New Radio Unlicensed (NR-U) and Wireless Gigabit (WiGig) links share an unlicensed millimeter-wave band. Our aim is to enhance the performance of coexisting networks by maximizing the overall network throughput via hybrid beamforming. This throughput is a function of both operators' medium access control protocols and physical layer parameters. To maximize the overall network throughput we propose a novel hidden node aware hybrid beamforming design. The hybrid precoders and combiners are optimal in the sense that they simultaneously maximize the signal power at desired users while minimizing the received inter-cell and intra-cell interferences at undesired users (leakage). The performance of the proposed scheme is examined through simulation. A comparison among the proposed method, a beam-steering solution, and an optimal unconstrained precoding design indicates the efficiency of the proposed algorithm.

To meet the ever-growing demands of data throughput for forthcoming and deployed wireless networks, new wireless technologies like Long-Term Evolution License-Assisted Access (LTE-LAA) operate in shared and unlicensed bands. However, the LAA network must co-exist with incumbent IEEE 802.11 Wi-Fi systems. We consider a coexistence scenario where multiple LAA and Wi-Fi links share an unlicensed band. We aim to improve this coexistence by maximizing the key performance indicators (KPIs) of these networks simultaneously via dimension reduction and multi-criteria optimization. These KPIs are network throughputs as a function of medium access control protocols and physical layer parameters. We perform an exploratory analysis of coexistence behavior by approximating active subspaces to identify low-dimensional structure in the optimization criteria, i.e., few linear combinations of parameters for simultaneously maximizing KPIs. We leverage an aggregate low-dimensional subspace parametrized by approximated active subspaces of throughputs to facilitate multi-criteria optimization. The low-dimensional subspace approximations inform visualizations revealing convex KPIs over mixed active coordinates leading to an analytic Pareto trace of near-optimal solutions.

Future unlicensed spectrum sharing scenarios involve multi-cell, multi-tier access of incumbent and emerging wireless systems, such as wireless local area network (WLAN), New-Radio unlicensed (NR-U), and Long-Term Evolution (LTE) with Licensed-Assisted Access (LAA). Listen-before-talk (LBT) medium access control (MAC) is a common technique used for channel sensing and access control. Despite intense research efforts, the majority of available results have not accurately analyzed multi-cell LBT with imperfect spectrum sensing. Furthermore, while past studies involved two major spectrum sharing strategies - shared cell access (SCA) and exclusive cell access (ECA), they missed a systematic comparison between the two. In this paper, we develop a unified analytical approach which maps the effects of imperfect spectrum sensing and multi-cell, multi-tier LBT to the key performance indicators (KPIs) of LAA and WLAN cells. We provide an analytical comparison between the SCA and ECA schemes, and show that the SCA can provide a significantly higher system throughput than the ECA as a function of sensing thresholds. We program the SCA and ECA algorithms with a new simulation method and implement Monte Carlo simulations, which verify our analytical results. Numerical results provide insightful observations on effects of various parameters. These results provide powerful analytical and simulation tools to evaluate the performance of multi-tier LBT coexistence systems with imperfect sensing, and effectively support coexistence system optimization.

Dynamic spectrum access (DSA) to achieve spectrum sharing in unlicensed bands is a promising approach for meeting the growing demands of forthcoming and deployed wireless networks, such as long-term evolution license-assisted access (LTE-LAA) and IEEE 802.11 Wi-Fi systems. In this paper, we consider a coexistence scenario where multiple LAA and Wi-Fi links compete for spectrum sharing subchannel access. We introduce a reinforcement-learning-based subchannel selection technique which allows access points (APs) and eNBs to select best subchannel distributively considering their medium access control (MAC) channel access protocols along with the physical layer parameters. The performance of this scheme is investigated through simulations, including the convergence property and sum throughput. Numerical results show that the proposed reinforcement-learning scheme converges fast and the sum throughput of the LAA and Wi-Fi systems is reasonably close to the result based on exhaustive search.

Carrier sense multiple access with collision avoidance (CSMA/CA) procedures have been specified for medium access control (MAC) in several incumbent and emerging wireless systems, such as wireless local area network (WLAN) and long-term evolution (LTE) with license assisted access (LAA). Clear channel assessment (CCA) errors in carrier sensing can cause significantly degraded network performance. Analyzing the impact of CCA errors in the MAC backoff and transmission process is a challenging task, and very few works have explicitly addressed this. Existing analytical work is only valid for special cases such as independent CCA errors, and the result lacks generality for extension to coexistence systems. In this paper, we try to fill this technical gap by modelling generalized CCA sensing errors which can be either fully correlated or independent due to the fading channel. We develop a new Markov model using matrix-vector representation which captures generalized CCA error events, and analyze the impact of CCA errors on the key performance indicators (KPIs), such as the throughput of both LTE-LAA and WLAN systems. To mitigate the effects of mis-detection and collisions which can cause the network throughput to drop to nearly zero, we propose a soft-collision method to reduce the performance loss. Finally, we program the LTE-LAA and WLAN CCA algorithms and implement extensive computer simulations. Comparisons between analytical and simulation results show consistent matching, and illustrate loss caused by sensing errors and improvement brought by the soft-collision method. This result provides a powerful analytical tool on CSMA/CA MAC-layer performance evaluation with imperfect sensing, applicable to both single and coexistence systems, and has practical value for countermeasure designs against sensing errors.

To improve spectrum sharing between long-term evolution (LTE) license assisted access (LAA) and incumbent systems such as wireless local area networks (WLANs) in unlicensed spectrum, listen before talk (LBT) has been proposed as a candidate for LAA channel access. To allow for a robust spectrum sensing performance, LBT may use a backoff-slot duration that is substantially larger than its WLAN counterpart. There is potential for an unknown backoff slot-jamming (SJ) effect, which may significantly decrease channel access probability (CAP) and throughput of LAA-LBT links. In this paper, we study the SJ effect and propose an effective anti-SJ (ASJ) LBT scheme. To gain theoretical insight, we develop a new performance analysis approach on coexisting systems with different slot durations. We model the LAA backoff process with super-counters, provide an in-depth analysis of the backoff process, and derive key performance indicator (KPI) statistics. These KPIs include backoff hold time, successful transmission probability, CAP, and throughput. Simulation results thoroughly validate our analytical results, and show that the ASJ-LBT scheme is effective in mitigating the SJ effect. These results fill a major technical gap in spectrum sharing research and may be extended to support system optimization and coexistence analysis of other heterogeneous systems.

To support efficient spectrum sharing and related standardization efforts in unlicensed spectrum, it is important to develop analytical tools to accurately quantify coexistence performance between long-term evolution license assisted access (LTE-LAA) and incumbent systems, such as wireless local area network (WLAN). Though joint throughput of spectrum sharing LTE-LAA and WLAN systems has been extensively studied, there lacks a systematic study on a high level metric - the probability of coexistence (PoC), which indicates whether coexistence is successful or not probabilistically. Another problem is that the majority of available results either ignored delay constraints, or studied only the mean (or variance) of delay, but have not considered the delay distribution and its impact on throughput. To address these problems, we define and analyze the original PoC metrics between LTE-LAA and WLAN systems based on two practical delay constraints. The first PoC is derived from the joint distribution probability of delays for successful transmissions; and the second PoC is defined upon the joint probability of delay-constrained throughput (DCT) of LAA and WLAN systems. To address the technical difficulties involved, we design a novel analytical framework to evaluate the moment generating function and cumulative distribution function (CDF) of the delay, and a new method to evaluate the DCT and its CDF. Consequently, the PoCs can be evaluated accurately with low complexity. The analytical results are verified by our Monte Carlo simulations, which demonstrate impacts of delay and throughput requirements on the PoCs, and illustrate design tradeoffs and insightful findings. These results provide theoretical and practical value for designing improved LTE-LAA and WLAN systems, and may be extended to other emerging spectrum sharing communication systems.

To enhance spectrum efficiency in next generation heterogeneous wireless systems, it is important to improve shared spectrum usage between unlicensed long-term evolution (LTE) systems, such as the license-assisted access (LAA), and legacy systems, such as wireless local area networks (WLANs). LTE-LAA uses listen-before-talk (LBT) schemes to enhance coexistence performance. However, available LAA-LBT schemes may incur several problems, such as a slot-jamming effect and a significant slot boundary tracking error, leading to degraded performance. In this paper, we develop an LBT scheme with improved design and software-defined radio (SDR)-based experimental procedure for a performance validation. We program the improved LBT algorithm in the SDR field-programmable gate array (FPGA), and compare the results with the original LBT algorithm. This work also presents an automated testing technique and new SDR functions that modify the LAA parameters in realtime (such as backoff idle slot durations). The experiment results confirm the predicted slot-jamming effect, and show that our improved design enhances LAA throughput. These results provide not only a more robust LAA-LBT design, but also a new method of SDR programming and testing, and insight into the coexistence performance of heterogeneous systems.

To enable constructive coexistence with wireless local area networks (WLANs), unlicensed long-term evolution (LTE) systems use listen before talk (LBT) as a major candidate technique. The LBT has a flexible backoff idle slot duration, which can be significantly larger than the WLAN counterpart. To our knowledge, however, available analytical results on the LTE and WLAN coexistence have considered only identical idle backoff slot durations. There is a formidable technical difficulty to coexistence analysis for different backoff slot durations. In this paper, we develop a new technical approach to address this open issue. First, we point out an LBT backoff slot jamming effect, and propose a modified LBT backoff scheme to address this problem. Second, for our proposed LBT scheme, we develop a new analytical framework to address system interactions with non-equal backoff slot durations, model the LTE backoff process as super-counters, and provide a thorough analysis on the throughput, backoff counter hold time, and successful transmission probabilities of LTE-LBT and WLAN systems. Finally, we program the algorithms and use computer simulation to validate the analysis. This result fills a major gap and provides practical value for LTE-LBT and WLAN coexistence performance analysis with heterogeneous sensing and backoff slot durations.