NeTS: Medium: Collaborative Research: Coexistence of Heterogeneous Wireless Access Technologies in the 5 GHz Bands

List of personnel

This is a multi-university project between Temple University, University of Arizona, and Virginia Tech.

Principal Investigators: Jie Wu and Xiaojiang Du (Temple University); Marwan Krunz (University of Arizona); Jung-Min (Jerry) Park (Virginia Tech).

Vision

Enabling harmonious spectrum sharing between heterogeneous wireless technologies is a challenging problem, but one that needs to be urgently addressed in order to quell the exploding demand for more spectrum by existing as well as burgeoning wireless applications. The main goal of this project is to develop advanced technologies for fair and efficient spectrum sharing between heterogeneous wireless technologies, including LTE-Unlicensed (LTE-U), Wi-Fi (802.11ac/802.11ax), and Dedicated Short-Range Communications (DSRC).

Specific Objectives

We conduct an in-depth study that focuses on two particular coexistence scenarios: (1) coexistence between LTE-U and Wi-Fi and (2) coexistence between vehicular wireless technologies and Wi-Fi. The specific objectives are:

(1) Avant-garde approaches for enabling LTE-U/Wi-Fi coexistence. We will develop and evaluate a simultaneous transmission-and-sensing technique that leverages the full-duplex (FD) and self-interference suppression capabilities of 802.11ax to mitigate interference due to coexisting wireless technologies. We will also develop an adaptive algorithm for switching between various modes at an FD-capable Wi-Fi device using rigorous mathematical models and simulation data. Finally, we will analyze the interactions between LTE-U and Wi-Fi subsystems and jointly adapt/optimize their interference mitigation control knobs using game-theoretic formulations.

(2) Backward-compatible approaches for enabling LTE-U/Wi-Fi coexistence. We will study backward-compatible techniques applicable to existing technologies, with a particular focus on techniques that enable fair spectrum sharing between Wi-Fi and LTE-U. These techniques include unilateral approaches that can be employed by LTE-U, à la Carrier Sensing Adaptive Transmission (CSAT), but with more proactive mechanisms for ensuring fairness. We will also investigate approaches that enable indirect communications between LTE-U and Wi-Fi networks to ensure fair access to the spectrum.

(3) Investigate Wi-Fi (legacy and emerging Wi-Fi technologies) and vehicular technologies that currently operate or are expected to operate in the U-NII and ITS bands at 5 GHz, including DSRC, C-V2X (also known as LTE-V or LTE-V2X), and Wi-Fi. We will investigate the new features of the emerging technologies, and evaluate their impact on legacy wireless systems that coexist in the same spectrum.

Broader Impacts

The collective expertise and experience of the PIs will ensure that the proposed research will not be a mere academic exercise, but rather a fruitful study that will produce findings which will serve as important references for implementing coexistence mechanisms and incumbent protection techniques for real-world spectrum sharing scenarios. Through industry and government outreach activities, the PIs will ensure that the project findings have maximum impacts on ongoing industry research/development efforts as well as on Government initiatives to open up more spectrum for spectrum sharing. The PIs will incorporate the outcomes of the project into courses currently offered at their respective institutions. The proposed work is expected to provide invaluable research experiences for the graduate students who will be involved in the project as well as produce high-quality hands-on exercises, project topics, and other pedagogical material that will enrich the undergraduate curriculum at the respective institutions.

Major Activities

  • The project addresses a number of different coexistence scenarios among heterogeneous wireless technologies that operate or are expected to operate in the 5 GHz bands, including Wi-Fi, unlicensed LTE, DSRC, and cellular vehicle to everything (C-V2X). These systems exhibit drastic differences in their channel access mechanisms, waveforms, interference tolerance and packet loss sensitivity, etc. Accordingly, solutions developed for one coexistence scenario are not likely to work for another.
  • The major activities carried out by the Temple team are summarized below.
  • In dynamic spectrum access (DSA), secondary transmitters (SU-TX) should only be allowed to transmit on a licensed channel belonging to incumbent users (IU) when the signal-to-interference-noise ratio (SINR) requirements of both IUs and SUs can be satisfied at the same time. However, in many DSA systems, the location and interference level of an IU are often considered sensitive data that should not be revealed, making it very challenging to ensure the QoS of both the IU and SUs while protecting IU operation security. In this work, we design a novel distributed SU transmit power control algorithm to solve this challenge.

  • To address the coexistence of LTE-U and Wi-Fi, we propose a novel mechanism that enables Wi-Fi and LTE systems fair coexistence in unlicensed spectrums by indirect communications between Wi-Fi’s AP and LTE’s BS: via the AP of the LTE provider. We formulate a constraint optimization problem to maximum the total amount of data transmitted in a communication cycle by adjusting the transmission time of Wi-Fi and LTE networks under the condition of fairness.

  • In Year 4 of the project, Wu (PI) and Du (Co-PI) at Temple University focused on coexistence of LTE-U and Wi-Fi in 5Ghz bands.

  • To address the coexistence of LTE-U and Wi-Fi, we propose a novel mechanism that enables Wi-Fi and LTE systems fair coexistence in unlicensed spectrums by indirect communications between Wi-Fi’s AP and LTE’s BS: via the AP of the LTE provider. We formulate a constraint optimization problem to maximum the total amount of data transmitted in a communication cycle by adjusting the transmission time of Wi-Fi and LTE networks under the condition of fairness.

  • One important application of LTE and Wi-Fi wireless networks is the vehicular networks. In another work, we study the problem of how to efficiently utilizing spectrum resources in vehicular networks. In this work, we leverage a cloud radio access network (C-RAN)-based vehicular network architecture, named C-VRAN, to facilitate efficient spectrum management and processing of vehicular networks.

  • In Year 3 of the project, Wu (PI) and Du (CoPI) at Temple University focused on coexistence of LTE-U and WiFi in 5Ghz bands.

  • To solve the issue of scarce spectrum resources of the existing cellular network, LTE-U expands LTE service to the unlicensed 5GHz spectrum. However, the centralized medium access control protocol of LTE largely decreases the performance of Wi-Fi networks operating in the same unlicensed spectrum. In the research, we propose a new mechanism based on the duty-cycle method. It can adaptively adjust the percentage of the airtime used by a LTE Small cell Base Station (SBS) according to the bandwidth of the licensed spectrum of the SBS and downlink data rate demands of the SBS users to maximize throughput of the SBS network on the unlicensed spectrum while ensuring fairness between the Wi-Fi and SBS network.

  • In another work, we propose a novel mechanism which can enable Wi-Fi and LTE systems fair coexistence in unlicensed spectrums by indirect communications between Wi-Fi’s AP and LTE’s BS: via the AP of the LTE provider. We formulate a constraint optimization problem to maximum the total amount of data transmitted in a communication cycle by adjusting the transmission time of Wi-Fi and LTE networks under the condition of fairness.

  • Cognitive radio networks (CRNs), offering novel network architecture for utilizing spectrum, have attracted significant attention in recent years. In CRNs, secondary users (SUs) first determine the status of a channel; if it is free, they start transmitting. If the status determination is wrong, SUs may unnecessarily interfere with the licensed primary user (PU). In cooperative spectrum sensing, a SU makes a decision about the presence of the PU based on its own and other SUs’ sensing results. Malicious SUs (MSUs) send false sensing results to SUs so that they make wrong decisions about the PU presence. As a result, a SU may transmit during the presence of the PU or may keep starving for the spectrum.

  • One of the most prominent cellular technologies, Long Term Evolution (LTE), is currently operating on some 800MHz, 2GHz, and 3.5GHz licensed bands. Wi-Fi is currently operating on 2.5GHz and 5GHz unlicensed bands. The declaration stating that 5GHz bands are unlicensed enables LTE to operate on 5GHz bands. It is challenging, however, for different wireless technologies to co-exist. The two standards, LTE-U and LTE-LAA, for LTE to coexist with Wi-Fi on the 5GHz band have evolved. The LTE-U standard is based on the duty cycle, while LTE-LAA is based on listen-before-talk (LBT). In existing LTE-U systems, the LTE base station (eNB) estimates the fair portion of Wi-Fi usage based on channel state information. The usage estimation from channel state information is not as accurate enough as well as the fair portion. So the challenge is how to collect Wi-Fi usage information so LET-U can make sensible decision to achieve fairness between LTE-U and Wi-Fi usage, while maintaining overall efficiency.

  • The project addresses a number of different coexistence scenarios among heterogeneous wireless technologies that operate or are expected to operate in the 5 GHz bands, including Wi-Fi, unlicensed LTE, DSRC, and cellular vehicle to everything (C-V2X). These systems exhibit drastic differences in their channel access mechanisms, waveforms, interference tolerance and packet loss sensitivity, etc. Accordingly, solutions developed for one coexistence scenario are not likely to work for another.

  • The research tasks were divided among the three research teams, with Virginia Tech (VT) focusing on the coexistence between Wi-Fi and the vehicular wireless technologies (DSRC and C-V2X) (upper part of the 5 GHz band), and Temple and Univ. of Arizona (UA) focusing on the LTE-Wi-Fi coexistence. The research agenda includes both avant-garde as well as backward-compatible approaches. The UA team has primarily been focusing on the former type, leveraging full-duplex capabilities that are envisioned to be integrated in future Wi-Fi systems (particularly, access points). The Temple team has primarily been focusing on backward-compatible approaches for LTE/Wi-Fi coexistence (e.g., CSAT), but with more proactive mechanisms for ensuring fairness. Once these efforts have reached an acceptable level of maturity, the team will explore the interactions between the various scenarios as well as the cost/benefit tradeoffs between competing solutions.

  • The investigators from the three universities have started to collaborate on different aspects of the project, although such collaborations have not yet resulted in jointly coauthored work. Furthermore, all four PIs have been exploring new protocols to communicate coexistence information via undefined header fields and through PHY-layer techniques (e.g., LTE-specific sensing). New criteria/definitions for fairness for coexistence of heterogeneous systems in the 5 GHz bands are also being collaboratively explored. We anticipate a few papers coauthored by all members of the team in the near future. To ensure proper followup, the team members will have a monthly telecon, and will also meet in person during the BWAC meetings as well as other major conferences, such as Infocom.

  • Wu (PI) and Du (Co-PI) at Temple University studied LTE-U and Wi-Fi coexistence in unlicensed spectrum scenario. Introducing LTE into a free, unlicensed spectrum will inevitably bring the problems of competing and coexisting with other unlicensed communications technologies in the same spectrum. In traditional communication technologies using unlicensed spectrum for data transmission, as represented by Wi-Fi, access channels can only be accessed through a competitive way in order to realize spectrum sharing. The LTE designed in the licensed spectrum has the absolute control over the spectrum. It performs the centralized scheduling of the wireless resource through the base station, so as to obtain higher spectral efficiency. Obviously, if the unlicensed spectrum is used as a new spectrum of LTE, the transmission of LTE-U will cause serious interference to Wi-Fi due to the channel detection and back off mechanism of Wi-Fi. Therefore, for the two systems with completely different time slots and scheduling modes, it is necessary to additionally design reasonable and fair coexistence in order to ensure both in the conditions of good transmission in the unlicensed spectrum. In this work, we study the coexistence of LTE-U and Wi-Fi systems in unlicensed spectrum scenario.

  • 5G is envisioned to consist of various types of Radio Access Technologies (RATs) (such as millimeter wave communication, LTE and Wi-Fi). For emerging and promising 5G mobile services, despite their diverse application scenarios, it is widely agreed that they share a common primary requirement: high data rate and high reliability. To meet such requirement, evolving wireless techniques and novel network infrastructures for 5G are needed. We believe that the Concurrent Multipath Transfer (CMT) technology could also contribute to the fulfillment of needs of 5G mobile services. CMT not only can improve communication throughput, but also provide communication reliability. CMT in 5G scenarios will pool multiple heterogeneous wireless resources by employing a variety of RATs concurrentl. The bandwidth of the RATs will be aggregated, achieving higher throughput.

  • The rapid growth of mobile network traffic has posed a serious challenge to the limited spectrum. The United States Federal Communications Commission (FCC) allowed the utilization of unused TV White Space (TVWS) by unlicensed secondary users (SUs). Particularly, the IEEE 802.19.1 standard is proposed to regulate the coexistence of dissimilar or independently operated SU networks and devices on the TV band. When multiple wireless networks attempt to share the same spectrum band in the same area, their coexistence may lead to a huge imbalance of bandwidth gain and collisions because (1) the difference in spectrum access design gives them an inherent advantage/disadvantage when competing with each other; (2) networks operated by independent entities cannot communicate to coordinate their access. In this work, we design efficient fair spectrum allocation for co-existing heterogeneous secondary user networks.

  • Wu (PI) and Du (Co-PI) at Temple University focused on coexistence of LTE-U and Wi-Fi in 5Ghz bands where some mobile operators having both LTE and Wi-Fi coverage exist. In existing LTE-U systems, LTE base station uses usage estimation of Wi-Fi based on channel state information to determine fair portion of usage. The usage estimation from channel state information is not accurate enough as well as the fair portion. In this research, a study of the fair coexistence between LTE-U and Wi-Fi in the scenario where an LTE eNB can exchange information with Wi-Fi access points (AP) was conducted. The communication is done in both wired and wireless medium. The wired medium is ethernet point-to-point communication, and the wireless communication is done using the reserved bits in Wi-Fi packets. Both ways are applicable to the operator, who has both LTE and Wi-Fi coverage. A Wi-Fi AP collect information about other operators’ APs and send to its LTE eNB. The LTE eNB adjusts its parameters (mainly duty cycle) according to the received information to achieve fairness. The adjustment of duty cycle is done in two ways: progressive and linear. In the progressive adjustment, the duty cycle is increased (decreased) by a factor, and in the linear adjustment, the duty cycle is increased (decreased) by a constant. When the throughput difference of LTE and Wi-Fi is greater (or smaller) than a threshold progressive (or linear) adjustment is applied.

  • In Year 2 of the project, Park (PI) and his graduate research assistants (GRAs) at Virginia Tech have been focusing on Wi-Fi (legacy and emerging Wi-Fi technologies) and vehicular technologies that currently operate or are expected to operate in the 5 GHz bands, including DSRC and C-V2X (also known as LTE-V or LTE-V2X). Specifically, they have been investigating the following issues: (1) viability of Wi-Fi’s channelization and its impact when coexisting with DSRC; (2) Wi-Fi’s impact on the performance of vehicular safety applications; (3) performance comparison between C-V2X and DSRC; (4) spectrum sharing between Wi-Fi and C-V2X; and (5) coexistence between legacy Wi-Fi (e.g., 802.11n/ac) and next-generation Wi-Fi, known as 802.11ax.

  • For the first problem, a study performed by Park et al. showed that under the current 802.11ac standard, not all of the Wi-Fi channelizations (i.e., channel and bandwidth combinations) can be used by 802.11ac devices without causing significant interference to DSRC nodes. Under these channelization constraints, they proposed a Real-time Channelization Algorithm (RCA) to maximize the throughput of Wi-Fi APs operating in shared spectrum. Findings were reported in a paper published in the proceedings of the 2017 IEEE INFOCOM. For the second problem, Park and his team developed an analytical model that provides insights on the performance of a DSRC network and its vulnerability to interference induced by other DSRC networks as well as 802.11ac networks. Using the analytical results derived from the model and extensive simulation results, they also proposed a methodology for adjusting 802.11ac parameters in order to enable a DSRC network to meet the performance requirements of safety applications. Findings were reported in a paper published in the proceedings of the 2017 IEEE ICC. Park’s team have recently begun to study the third, fourth, and fifth problems. For the third problem, they are currently focusing on the MAC-layer performance of the two technologies under various traffic conditions using NS-3 simulation results. The C-V2X technology has been garnering increasing attention from the automotive and wireless industries as well as from the spectrum regulatory entities around the world. In the USA, if C-V2X is adopted, then it is highly likely that it will operate somewhere in the Intelligent Transportation System (ITS) band of 5.9 GHz (5.85-5.925 GHz). In that case, C-V2X may need to coexist with unlicensed wireless systems, such as Wi-Fi. For the fourth issue, Park’s team is investigating the impact of Wi-Fi on C-V2X’s performance, and plan to utilize the findings to develop effective coexistence mechanisms. In the UNII bands at 5 GHz, a number of different Wi-Fi technologies, including 802.11n and 802.11ac, currently coexist. In the near future, however, these Wi-Fi legacy technologies will need to coexist with yet another Wi-Fi technology, referred to as IEEE 802.11ax. The new amendment to the 802.11 set of standards introduces OFDMA to improve overall spectral efficiency, and higher order 1024 QAM modulation support for increased throughput. For the fifth problem, Park and his graduate students are evaluating the new features of 802.11ax, and studying their potential impact on the performance of legacy Wi-Fi technologies that coexist in the same band. Specifically, they are currently focusing on the uplink OFDMA (orthogonal frequency division multiple access)-based random access protocol for facilitating random access transmissions in the uplink.

  • Krunz (PI) and his team at the University of Arizona focused their efforts on studying the coexistence of LTE and Wi-Fi in the 5 GHz bands. Specifically, they proposed a modified Wi-Fi operation mode in which Wi-Fi stations (STAs) exploit full-duplex (FD) communications to enable simultaneous transmission and sensing (TS) so as to reduce the time required to detect collision with LTE signals. The FD-based detection framework makes it possible to differentiate between Wi-Fi and LTE-U signals. By harnessing salient cyclo-stationary features in LTE-U signals, the team developed a simple detector that takes advantage of the cyclic prefix in LTE waveforms (see Figures 1 & 2) to achieve high detection accuracy. The statistics of the detection scheme were derived and its misdetection and false-alarm probabilities were analyzed, considering various channel conditions and FD capabilities (e.g., varying degrees of self-interference suppression). A Neyman Pearson (NP) detection rule was also derived.

  • The proposed detection scheme makes it possible to identify the type of interference (i.e., LTE signal versus something else) at a Wi-Fi station, paving the way to study another problem related to selecting the clear channel assessment (CCA) threshold for LTE signals. IEEE 802.11 standards assign specific CCA threshold values for detecting Wi-Fi and non-Wi-Fi signals, as explained in Figure 3, however, the standards follow a conservative threshold for LTE signals based on energy detection) because of the inability of Wi-Fi to identify LTE interference. During the past year, we have studied the optimal (fair) CCA threshold that Wi-Fi should use when coexisting with a duty cycled LTE-U.

  • Another research activity that the UA team pursued is related to rate/mode adaptation in an LTE/Wi-Fi coexistence scenario. Specifically, an FD-enabled Wi-Fi station can transmit and receive (TR mode) data simultaneously to increase the link throughput, or transmit and sense (TS mode) simultaneously to monitor the LTE-U activity. We modeled the LTE-U interference as a hidden Markov process, and solved the problem of jointly adapting Wi-Fi rates/duplicity modes using partially observable Markov decision process (POMDP). We also presented a finite state Markov channel (FSMC) model that incorporates the process of LTE-U duty cycling. The two-sliding-windows correlator was incorporated in the TS mode to better drive the adaptation process in response to LTE-U dynamics. We investigated various protocol changes and designs required to enable the new scheme in future IEEE 802.11 standards.

  • Another research activity that the UA team pursued is related to rate/mode adaptation in an LTE/Wi-Fi coexistence scenario. Specifically, an FD-enabled Wi-Fi station can transmit and receive (TR mode) data simultaneously to increase the link throughput, or transmit and sense (TS mode) simultaneously to monitor the LTE-U activity; see Figure 4. We modeled the LTE-U interference as a hidden Markov process, and solved the problem of jointly adapting Wi-Fi rates/duplicity modes using partially observable Markov decision process (POMDP). We also presented a finite state Markov channel (FSMC) model that incorporates the process of LTE-U duty cycling.

    Significant Results

    The significant results are summarized below:

  • We develop a new privacy-preserving distributed DSA design. In this design, we formulate the coexistence problem between IU and SUs as a SU power control problem. We assume that ESC sensors sense the signal strength of IUs. The sensing results at an ESC sensor is converted into a scalar number that is sent to SAS. SAS integrates all the ESC's input and publishes a set of parameters that are computed based on ESC inputs. Each SUs adjusts its transmit power iteratively based on its local measurement of other SUs interference and the published parameters from SAS. We mathematically prove that the system converges to a stable point which guarantees that IU will not be harmed by SU interference and SUs can achieve their desired SINR. Simulation results show that our system converges very fast. In addition, since the ESC never store and send the raw sensing data of IU and the number it sends to SAS cannot be used to derive IU location. Similarly, the information published by the SAS also cannot be used to derive the location of IUs, This ensures that the location privacy of IUs will be protected in this distributed DSA design. We classify this method as a distributed DSA design because the spectrum allocation and transmit power of each SU is not directly controlled by SAS. SAS only serves as a bulletin board that publish global information that is not specific to any SU. The algorithm relies on the distributed and iterative power control algorithm in the SUs mostly for transmit power and resource allocation. The work has been submitted to the IEEE Transactions of Mobile Computing, and it is currently under major revision.
  • To enable Wi-Fi and LTE-U fair coexistence in unlicensed spectrums, we propose a novel mechanism that is able to set up indirect communications between Wi-Fi and LTE systems. In addition, we formulate the fair coexistence of Wi-Fi and LTE systems in unlicensed spectrums as a constrained optimization problem with the objective to maximize the total amount of data transmitted by Wi-Fi and LTE systems in a communication cycle. We are able to solve the constrained optimization problem and obtain the optimum solution. We evaluate the performance of the proposed scheme via NS-3 simulations. The simulations results show that the proposed mechanism and approaches can effectively ensure the fair coexistence of Wi-Fi and LTE-U systems and improve the total system throughput. This work has been published in the Elsevier journal of Future Generation Computer Systems in Nov. 2020.
  • Publications

    Books

    1. W. Chang and J. Wu, "Fog/Edge Computing For Security, Privacy, and Applications, " Springer, 2021.

    2. R. Biswas and J. Wu, "Cognitive Radio Networks (CRN) Technologies and Applications,"Emerging Wireless Communication and Network Technologies: Principle, Paradigm and Performance (Chapter 2), K. Arya, R. Bhadoria, N. Chaudhari (eds), Springer Link Library, 2018.

    Journal

    1. Z. Guo, M. Li, and M. Krunz, “Exploiting Successive Interference Cancellation for Spectrum Sharing over Unlicensed Bands,” accepted to appear in IEEE Transactions on MobileComputing (TMC), Apr. 2023 .

    2. Z. Zhang, H. Rahbari, and M. Krunz, “Adaptive Preamble Embedding with MIMO to Support User-defined Functionalities in WLANs,” IEEE Transactions on Mobile Computing (TMC), vol. 22, no. 2, pp. 691-707, Feb. 2023, doi: 10.1109/TMC.2021.3095459.

    3. Y. Xiao, R. Xia, Y. Li, G. Shi, D. N. Nguyen, D. T. Hoang, D. Niyato, and M. Krunz, “Distributed Traffic Synthesis and Classification in Edge Networks: Federated Self-Supervised Learning Approach,” accepted to appear in IEEE Transactions on Mobile Computing (TMC), Jan. 2023

    4. M. Moghadam, B. Boroomand, M. Jalali, A. Zareian, A. Daeijavad, M. Hossein Manshaei, and M. Krunz, “Games of GANs: Game-theoretical models for generative adversarial networks,” accepted to appear in Artificial Intelligence Review, Jan. 2023

    5. Y. Xiao, X. Zhang, Y. Li, G. Shi, M. Krunz, D. Nguyen, and D. T. Hoang, “Time-sensitive learning for heterogeneous federated edge intelligence,” accepted to appear in IEEE Transactions on Mobile Computing (TMC), Jan. 2023.

    6. Y. Lin, P. Qiu, Y. Yang, X. Du, and J. Wu, “Distributed and Secure Power Control for Secondary Users in Dynamic Spectrum Access,” accepted to appear in IEEE Transactions on Wireless Communications (TWC), 2022.

    7. I. Shaban, X. Han, L. Lazos, M. Li, Y. Xiao, and M. Krunz, “Misbehavior Detection in Wi-Fi/LTE Coexistence Over Unlicensed Bands,” accepted to appear in the IEEE Transactions on Mobile Computing (TMC), DOI: 10.1109/TMC.20223164326.

    8. Y. Xiao and M. Krunz, “AdaptiveFog: A Modeling and Optimization Framework for Fog Computing in Intelligent Transportation Systems,” IEEE Transactions on Mobile Computing (TMC), Vol. 21, Issue. 12, pp. 4187-4200, 1 Dec. 2022, doi: 10.1109/TMC.2021.3080397.

    9. K. Chi, X. Du, G. Yin, J. Wu, M. Guizani, Q. Han, and Y. Yang, “Efficient and Fair Wi-Fi and LTE-U Coexistence via Communications over Content Centric Networking,” Future Generation Computer Systems, Vol. 112, Pages 297-306, Nov. 2020.

    10. Q. Wang, X. Du, Z. Gao, and M. Guizani, “An Optimal Channel Occupation Time Adjustment Method for LBE in Unlicensed Spectrum,” IEEE Transactions on Vehicular Technology, Vol 68, Issue 11, pp. 10943 – 10955, November. 2019, DOI: 10.1109/TVT.2019.2940123.

    11. Y. Su, X. Lu, L. Huang, X. Du, and M. Guizani, “A Novel DCT-Based Compression Scheme for 5G Vehicular Networks,” IEEE Transactions on Vehicular Technology, Vol 68, Issue 11, pp. 10872-10881, November. 2019, DOI: 10.1109/TVT.2019.2939619.

    12. Q. Wang, X. Du, Z. Gao, and M. Guizani, ”An Optimal Synchronous LBE-based Medium Access Mechanism for Throughput Maximization and Fairness Assurance,” IEEE Transactions on Vehicular Technology, accepted.

    13. K. Chi, X. Du, G. Yin, M. Guizani, Enabling Wi-Fi and LTE-U fair coexistence in unlicensed spectrums by the communication, IEEE Transactions on Vehicular Technology, submitted.

    14. Y, Dai, J. Wu and X. Du, "Hierarchical and Hybrid: Mobility-compatible Database-assisted Framework For Dynamic Spectrum Access," IEEE Transactions on Network Science and Engineering (TNSE), Vol 7, Issue 1, pp. 216--226, 2018, DOI: 10.1109/TNSE.2018.2832021.

    15. J. Song, P. Dong, H. Zhou, T. Zheng, X. Du, M. Guizani, “A Performance Analysis Model of TCP over Multiple Heterogeneous Paths for 5G Mobile Services”, MDPI Sustainability Journal, April 2018, DOI:10.3390/su10051337.

    16. G. Naik, J. Liu, and J. Park, “Coexistence of Wireless Technologies in the 5 GHz Bands: A Survey of Existing Solutions and a Roadmap for Future Research,” IEEE Communications Surveys and Tutorials, Mar. 2018, DOI: 10.1109/COMST.2018.2815585.

    17. S. Bhattarai, P. R. Vaka, and J. Park, “Thwarting location inference attacks in database-driven spectrum sharing,” IEEE Transactions on Cognitive Communications and Networking, Vol 4, Issue 2, pp. 314–327, June 2018, DOI: 10.1109/TCCN.2017.2785770.

    18. W. Afifi, M. Abdel-Rahman, M. Krunz, and A. B. MacKenzie, “Full-duplex or half-duplex: A Bayesian Game for Wireless Networks with Heterogeneous Self-Interference Cancellation Capabilities,” IEEE Transactions on Mobile Computing, Vol. 17, Issue. 5, pp. 1076-1089, May 2018.

    19. M. Hirzallah, W. Afifi, and M. Krunz, "Provisioning QoS in Wi-Fi Systems with Asymmetric Full-duplex Communications," submitted to the IEEE Transactions on Cognitive Communications and Networks (TCCN), April 2018.

    20. Y. Xiao, M. Hirzallah, and M. Krunz, “Distributed Resource Allocation for Network Slicing over Licensed and Unlicensed Bands,” submitted to the IEEE Journal on Selected Areas of Communications (JSAC), April 2018.

    21. D. Nguyen, E. Dutkiewicz, and M. Krunz, “Harvesting short-lived white spaces via opportunistic traffic offloading between mobile service providers,” accepted for publication in the IEEE Transactions on Cognitive Communications and Networking (TCCN).

    22. Z. Khan, J. Lehtomaki, S. Scott, Z. Han, M. Krunz, and A. Marshall, “Distributed and coordinated spectrum access methods for heterogeneous channel bonding,” IEEE Transactions on Cognitive Communications and Networks (TCCN), Vol. 3, Issue. 3, pp. 267-281, Sep. 2017.

    23. W. Afifi and M. Krunz, “TSRA: An adaptive mechanism for switching between communication modes in full-duplex opportunistic spectrum access systems,” IEEE Transactions on Mobile Computing, Vol. 16, Issue. 6, pp. 1758–1772, June 2017.

    24. M. Hirzallah, W. Afifi and M. Krunz, "Full-Duplex-Based Rate/Mode Adaptation Strategies for Wi-Fi/LTE-U Coexistence: A POMDP Approach," IEEE Journal on Selected Areas in Communications, Vol. 35, Issue. 1, pp. 20-29, Jan. 2017.

    Conference

    1. M. Feng, W. Zhang, and M. Krunz, "Dynamic Spectrum Access in Non-Stationary Environments: A DRL-LSTM Integrated Approach", Proc. of the International Conference on Computing, Networking and Communications (ICNC): AI and Machine Learning for Communications and Networking, Feb. 2023

    2. Z. Zhang and M. Krunz, "SIGTAM: A Tampering Attack on Wi-Fi Preamble Signaling and Countermeasures", Proc. of the IEEE Conference on Communications and Network Security (CNS), Austin, Texas, Oct. 2022.

    3. A. Yazdani-Abyaneh and M. Krunz, “Automatic Machine Learning for Multi-Receiver CNN Technology Classifiers,” Proc. of the ACM Workshop on Wireless Security and Machine Learning (WiseML), San Antonio, Texas, May. 2022.

    4. W. Zhang and M. Krunz, "Machine Learning based Protocol Classification in Unlicensed 5 GHz Bands," Proc. of the IEEE ICC 2022 Conference - Workshop on Spectrum Sharing Technology for Next Generation Communications, Seoul, South Korea, May. 2022.

    5. M. Krunz and W. Zhang, “Application of Adversarial Machine Learning in Protocol and Modulation Misclassification,” Proc. of the Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications Conference (part of SPIE Defense and Commercial Sensing Symposium), Orlando, FL, April. 2022.

    6. R. Biswas and J. Wu, "Protecting Resources Against Volumetric and Non-volumetric Network Attacks," Proc. of the IEEE International Conference on Parallel and Distributed Systems (ICPADS 2021), Dec 14-16, 2021.

    7. R. Biswas, J. Wu, and X. Du," Mitigation of the Spectrum Sensing Data Falsifying Attack in Cognitive Radio Networks, " Proc. of the IEEE International Conference on Communications (IEEE ICC 2019), May 20-24, 2019.

    8. R. Biswas and J. Wu," Co-existence of LTE-U and Wi-Fi with Direct Communication, " Proc. of the IEEE International Conference on Communications (IEEE ICC 2019), May 20-24, 2019.

    9. Q. Wang, Z. Gao, X. Du, and L. Zhu, "An Optimal LTE-U Access Method for Throughput Maximization and Fairness Assurance," in Proc. of IEEE IPCCC 2018, Florida, USA, Nov. 2018.

    10. K. Chi, L. Wu, X. Du, G. Yin, J. Wu, B. Ji, and X. Hei, “Enabling Fair Spectrum Sharing between Wi-Fi and LTE-Unlicensed,” in Proc. of IEEE ICC 2018, Kansas City, USA, May 2018.

    11. R. Biswas and J. Wu, "Co-existence of LTE-U and Wi-Fi with Direct Communication," submitted to GLOBECOM 2018 - 2018 IEEE Global Communications Conference, Abu Dhabi, 2018.

    12. G. Naik, S. Bhattarai and J. Park, “Performance Analysis of Uplink Multi-User OFDMA in IEEE 802.11ax,” 2018 IEEE Int’l Conference on Communications (ICC), Kansas City, MO, USA, May 2018.

    13. H. Rahbari, P. Siyari, M. Krunz, and J. Park, “Adaptive demodulation for wireless systems in the presence of frequency-offset estimation errors,” IEEE International Conference on Computer Communications (INFOCOM), Honolulu, USA, Apr. 2018.

    14. S. Bhattarai, P. Vaka, and J. Park, “Coexistence of NB-IoT and radar in shared spectrum: An experimental study,” IEEE Global Communications Conference (GLOBECOM), Singapore, Dec. 2017.

    15. G. Naik, J. Park, S. Das, I. Vukovic, and J. Rao, “LTE-V and DSRC: State of the art, coexistence, and future evolution,” under review.

    16. G. Naik, S. Bhattari, and J. Park, “Toward increasing the random access efficiency of multi-user OFDMA in IEEE 802.11ax,” under review.

    17. Y. Xiao, M. Hirzallah, and M. Krunz, “On Modeling and Optimizing LTE/Wi-Fi Coexistence with Prioritized Traffic Classes," submitted to IEEE DySPAN 2018.

    18. I. Samy, L. Lazos, Y. Xiao, M. Li, and M. Krunz, “LTE misbehavior detection in Wi-Fi/LTE coexistence under the LAA-LTE standard,” accepted for the 11th ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec 2018), June 2018, Stockholm, Sweden (long paper).

    19. Y. Xiao, M. Hirzallah, and M. Krunz, "Optimizing Inter-operator Network Slicing over Licensed and Unlicensed Bands," Proc. of the IEEE SECON 2018 Conference, Hong Kong, June 2018.

    20. M. Hirzallah, W. Afifi, and M. Krunz, "Joint mode and rate adaptation for asymmetric full-duplex communications in WLANs," Proc. of the IEEE ICC 2018 Conference, Kansas City, Kansas, May 2018.

    21. M. Hirzallah, Y. Xiao, M. Krunz, “MatchMaker: Stable and Fair Multi-Operator Channel Sharing Framework for Harmonious LTE/Wi-Fi Coexistence,” in preparation for submission to INFOCOM’18.

    Other Publications

    1. M. Hirzallah, W. Afifi and M. Krunz, "Full-Duplex Adaptation Strategies for Wi-Fi/LTE-U Coexistence," University of Arizona, Department of ECE, TR-UA-ECE-2016-3 (last updated: Nov 18, 2016).

    Patents

    1. M. Krunz, W. Afifi and M. Hirzallah, "A Method for Adapting the Clear Channel Assessment Threshold to Support Wi-Fi/LTE-U Coexistence," Invention Disclosure, Tech Launch Arizona, file-16-227, 2016.