On Modeling and Optimizing LTE/Wi-Fi Coexistence with Prioritized Traffic Classes

© 2018 IEEE. The dramatic growth in demand for mobile data service has prompted mobile network operators (MNOs) to explore new spectrum resources in unlicensed bands. MNOs have been recently allowed to extend LTE-based service called LTE-LAA over 5 GHz U-NII bands, currently occupied by Wi-Fi. To support applications with diverse QoS requirements, both LTE and Wi-Fi technologies introduce multiple priority classes with different channel contention parameters for accessing unlicensed bands. How these different priority classes affect the interplay between coexisting LTE and Wi-Fi technologies is still relatively under explored. In this paper, we develop a simple and efficient framework that helps MNOs assess the fair coexistence between MNOs and Wi-Fi operators with prioritized channel access under multi-channel setting. We derive an approximated close-form solution for each MNO to pre-evaluate the probability of successful transmission (PST), average contention delay, and average throughput when adopting different priority classes to serve different traffics. MNOs and Wi-Fi operators can fit our model using measurements collected offline and/or online, and use it to further optimize their systems' throughput and latency. Our results reveal that PSTs computed with our approximated closed-form model approach those collected from system-level simulations with around 95% accuracy under scenarios of dense network deployment density and high traffic intensity

Jamming attack on in-band full-duplex communications: Detection and countermeasures

© 2016 IEEE. Recent advances in the design of in-band full-duplex (IBFD) radios promise to double the throughput of a wireless link. However, IBFD-capable nodes are more vulnerable to jamming attacks than their out-of-band full-duplex (OBFD) counterparts, and any advantages offered by them over the OBFD nodes can be jeopardized by such attacks. A jammer needs to attack both the uplink and the downlink channels to completely break the communication link between two OBFD nodes. In contrast, he only needs to jam one channel (used for both uplink and downlink) in the case of two IBFD nodes. Even worse, a jammer with the IBFD capability can learn the transmitters' activity while injecting interference, allowing it to react instantly with the transmitter's strategies. In this paper, we investigate frequency hopping (FH) technique for countering jamming attacks in the context of IBFD wireless radios. Specifically, we develop an optimal strategy for IBFD radios to combat an IBFD reactive sweep jammer. First, we introduce two operational modes for IBFD radios: transmission reception and transmission-detection. These modes are intended to boost the anti-jamming capability of IBFD radios. We then jointly optimize the decision of when to switch between the modes and when to hop to a new channel using Markov decision processes. Numerical investigations show that our policy significantly improves the throughput of IBFD nodes under jamming attacks

Price-based friendly jamming in a MISO interference wiretap channel

© 2016 IEEE. In this paper, we expand the scope of PHY-layer security by investigating TX-based friendly jamming (FJ) for the wiretap channel in multi-link settings. For the single-link scenario, creating a TX-based FJ is an effective and practical method in improving the secrecy rate. In a multi-link setting, several information signals must be transmitted simultaneously. Thus, the design must guarantee that the FJ signal of a given transmitter does not interfere with unintended but legitimate receivers. Under the assumption of exact knowledge of the eavesdropping channel, we first propose a distributed price-based approach to improve the secrecy sum-rate of a two-link network with one eavesdropper while satisfying an information-rate constraint for both link. Simulations show that price-based FJ control outperforms greedy FJ, and is close to the performance of a centralized approach. Next, we propose a method based on mixed strategic games that can offer robust solutions to the distributed secrecy sum-rate maximization problem under the assumption of an unknown eavesdropping channel. Lastly, we use simulations to show that in addition to outperforming the greedy approach, our robust optimization also satisfies practical network considerations. In particular, the transmission time for the robust optimization can be determined flexibly to match the channel's coherence time

Cognitive Networks with In-Band Full-Duplex Radios: Jamming Attacks and Countermeasures

© 2015 IEEE. Although in-band full-duplex (IBFD) radios promise to double the throughput of a wireless link, they are more vulnerable to jamming attacks than their out-of-band full-duplex (OBFD) counterparts. For two communicating OBFD nodes, a jammer needs to attack both the uplink and the downlink channels to completely break the communication link. In contrast, only one common channel needs to be jammed in the case of two IBFD nodes. Even worse, a jammer with self-interference suppression (SIS) capabilities (the underlying technique of IBFD radios) can learn the transmitters' activity while injecting interference, allowing it to react instantly to the transmitter's strategies. In this work, we consider a power-constrained IBFD 'reactive-sweep' jammer that sweeps through the set of channels by jamming a subset of them simultaneously. We model the interactions between the IBFD radios and the jammer as a stochastic constrained zero-sum Markov game in which nodes adopt the frequency hopping (FH) technique as their strategies to counter jamming attacks. Beside the IBFD transmission-reception (TR) mode, we introduce an additional operation mode, called transmission-detection (TD), in which an IBFD radio transmits and leverages its SIS capability to detect jammers. The aim of the TD mode is to make IBFD radios more cognitive to jamming. The nodes' optimal defense strategy that guides them when to hop and which operational mode (TD or TR) to use is then established from the equilibrium of the stochastic Markov game. We prove that this optimal policy has a threshold structure, in which IBFD nodes stay on the same channel up to a certain number of time slots before hopping. Simulation results show that our policy significantly improves the throughput of IBFD nodes under jamming attacks

Optimizing inter-operator network slicing over licensed and unlicensed bands

© 2018 IEEE. Network slicing has been considered as a key enabling technology for 5G due to its ability to customize and "slice" a common resource to support diverse services and verticals. This paper introduces a novel inter-operator network slicing framework in which multiple mobile network operators (MNOs) can cooperate and jointly slice their accessible spectrum resources in both licensed and unlicensed bands. For the licensed band slicing, we propose the inter-operator spectrum aggregation method which allows two or more MNOs to cooperate and share their licensed bands to support a common set of service types. We then consider the sharing of unlicensed bands. Since all MNOs enjoy equal rights to access unlicensed bands, we introduce the concept of right sharing for MNOs to share and trade their spectrum access rights. We develop a modified back-of-the-envelop method for the MNOs to evaluate their value of rights when coexisting with other wireless technologies. We develop a network slicing game based on the overlapping coalition formation game to investigate the possible cooperation between MNOs. We prove that our proposed game always has at least one stable slicing structure that maximizes the social welfare. To evaluate the practical performance of our proposed framework, we develop a C++-based discrete-event simulator and simulate a possible implementation of our proposed framework over 400 base station locations deployed by two primary cellular operators in the city of Dublin. Numerical results show that our proposed framework can almost double the capacity for all supported services for each operator under certain conditions

Rolling preambles: Mitigating stealthy FO estimation attacks in OFDM-based 802.11 systems

© 2016 IEEE. Modern wireless systems and standards increasingly rely on OFDM for high-throughput communications. However, these systems are often highly vulnerable to selective jamming attacks, particularly when a jammer targets (part of) the known frame preamble. In this paper, we consider one of the most disruptive jamming attacks against the preamble-based frequency offset (FO) estimation in IEEE 802.11a/n/ac/ax systems and develop four techniques to mitigate this attack. Two of these techniques are based on randomly changing the first half of the standard frame preamble at the transmitter while maintaining its backward compatibility with legacy receivers. Specifically, we design a set of new preamble waveforms that satisfy the expected characteristics of a preamble in 802.11 systems. The other two techniques take a receiver-based approach and exploit the parts of the preamble that are not under attack to estimate the FO. We conduct extensive simulations and illustrative USRP experiments to study the effectiveness of these countermeasures

Sense-Bandits: AI-based Adaptation of Sensing Thresholds for Heterogeneous-technology Coexistence Over Unlicensed Bands

In this paper, we present Sense-Bandits, an AI-based framework for distributed adaptation of the sensing thresholds (STs) over shared spectrum. This framework specifically targets the coexistence of heterogenous technologies, e.g., Wi-Fi, 4G Licensed-Assisted Access (LAA), and 5G New Radio Unlicensed (NR-U), over unlicensed channels. To access the channel, a device compares the measured power with a predefined ST value and accordingly decides if the channel is idle or not. Improper setting of the ST values creates asymmetric sensing floors, resulting in collisions due to hidden terminals and/or reduction in the spatial reuse due to exposed terminals. Optimal ST setting is challenging because it requires global knowledge of mobility, traffic loads, and channel access behavior of all contending devices. Sense-Bandits tackles this problem by employing a clustering-based multi-armed bandit (MAB) algorithm, which adapts its learning behavior based on network dynamics. Clustering allows the algorithm to track network changes in real-time, ensuring fast learning of the best ST values by classifying the state and dynamics of coexisting networks. We develop a C++-based network simulator that implements Sense-Bandits and we apply it to evaluate the coexistence of Wi-Fi and 5G NR-U systems over the unlicensed 5 GHz U-NII bands. Our simulation results indicate that ST-adaptive devices employing Sense-Bandits do not harm neighboring devices that adopt a fixed ST value

Intelligent Tracking of Network Dynamics for Cross-Technology Coexistence Over Unlicensed Bands

Unlicensed bands offer great opportunities for numerous wireless technologies, including IEEE 802.11-based systems, 4G Licensed-Assisted-Access (LAA), and 5G New Radio Unlicensed (NR-U) networks. Achieving harmonious coexistence between these technologies requires real-time adaptation of their channel access, which can be facilitated by artificial intelligence (AI) and machine learning (ML) techniques. However, to leverage such techniques, we need to characterize the state of unlicensed wireless channel and the dynamics of the coexisting systems. In this paper, we introduce the concept of Sensing Fingerprint (SF) profile to characterize the state of coexisting networks and track their dynamics over unlicensed bands. We conduct extensive experiments to show the effectiveness of SF profile in tracking key network dynamics, including sensitivity thresholds of contending devices, their mobility, traffic loads, and other channel access parameters. AI-and ML-based controllers can utilize this tool to model the state of coexisting networks and track their dynamics