Related papers: MAC protocol classification in the ISM band using …
The existing medium access control (MAC) protocol of Wi-Fi networks (i.e., carrier-sense multiple access with collision avoidance (CSMA/CA)) suffers from poor performance in dense deployments due to the increasing number of collisions and…
Parking sensor network is rapidly deploying around the world and is regarded as one of the first implemented urban services in smart cities. To provide the best network performance, the MAC protocol shall be adaptive enough in order to…
The proliferation of wireless services and applications over the past decade has led to the rapidly increasing demand in wireless spectrum. Hence, we have been facing a critical spectrum shortage problem even though several measurements…
Automatic modulation classification (AMC) is a crucial stage in the spectrum management, signal monitoring, and control of wireless communication systems. The accurate classification of the modulation format plays a vital role in the…
Predictable network performance is key in many low-power wireless sensor network applications. In this paper, we use machine learning as an effective technique for real-time characterization of the communication performance as observed by…
As the demand of wireless communication continues to rise, the radio spectrum (a finite resource) requires increasingly efficient utilization. This trend is driving the evolution from static, stand-alone spectrum allocation toward spectrum…
The exponential growth of IoT devices and the demand of smart devices for higher data rates has heightened the need for sharing and managing spectrum resources in cellular 5G/6G operating in licensed bands and Wi-Fi technologies operating…
The desirability of the mid-band frequency range (1 - 10 GHz) for federal and commercial applications, combined with the growing applications for commercial indoor use-cases, such as factory automation, opens up a new approach to spectrum…
Beam management (BM) protocols are critical for establishing and maintaining connectivity between network radio nodes and User Equipments (UEs). In Distributed Multiple Input Multiple Output systems (D-MIMO), a number of access points…
This paper looks into the technology classification problem for a distributed wireless spectrum sensing network. First, a new data-driven model for Automatic Modulation Classification (AMC) based on long short term memory (LSTM) is…
Spectrum sensing is a fundamental component in cognitive radio. A major challenge in this area is the requirement of a high sampling rate in the sensing of a wideband signal. In this paper a wideband spectrum sensing model is presented that…
The Internet of Things (IoT) is expected to require more effective and efficient wireless communications than ever before. For this reason, techniques such as spectrum sharing, dynamic spectrum access, extraction of signal intelligence and…
In wireless networks, an essential step for precise range-based localization is the high-resolution estimation of multipath channel delays. The resolution of traditional delay estimation algorithms is inversely proportional to the bandwidth…
Multi-beam antenna technologies have provided lots of promising solutions to many current challenges faced in wireless mesh networks. The antenna can establish several beamformings simultaneously and initiate concurrent transmissions or…
Spectrum sharing mechanisms need to be carefully designed to enable inter-technology coexistence in the unlicensed bands, as these bands are an instance of a spectrum commons where heterogeneous technologies and deployments must coexist.…
In congested electromagnetic environments, cognitive radios require knowledge about other emitters in order to optimize their dynamic spectrum access strategy. Deep learning classification algorithms have been used to recognize the wireless…
Intrusion detection has become one of the most critical tasks in a wireless network to prevent service outages that can take long to fix. The sheer variety of anomalous events necessitates adopting cognitive anomaly detection methods…
This paper investigates deep neural networks for radio signal classification. Instead of performing modulation recognition and combining it with further analysis methods, the classifier operates directly on the IQ data of the signals and…
With the severe spectrum shortage in conventional cellular bands, millimeter-wave (mmWave) frequencies have been attracting growing attention for next-generation micro- and picocellular wireless networks. A fundamental and open question is…
Emerging wireless communication systems will be characterized by a tight coupling between communication and positioning. This is particularly apparent in millimeter-wave (mm-wave) communications, where devices use a large number of antennas…