ABSTRACT Since the opening of the 6 GHz bands for unlicensed radio access technologies (RATs), new coexistence mechanisms leveraging the currently uninhabited 6 GHz bands have been investigated, aiming for fair coexistence of Wi‐Fi 6 and 5G new radio unlicensed (NR‐U). However, our study shows that the utilization of the highly attractive 6 GHz bands can be significantly enhanced by exploring additional spectrum access opportunities, which remain unrealized in the existing channel contention mechanisms. We propose a novel two‐stage channel contention mechanism for the coexistence of Wi‐Fi 6 and 5G NR‐U in the 6 GHz bands to explore these missed spectrum access opportunities. We formulate the probability of interference to ongoing transmissions and utilize this probability to enhance the utilization of radio resources by allowing simultaneous transmissions on a channel. We incorporate cross‐technology communication (CTC) to compute this probability and formulate an optimization problem to derive the optimal CTC information required for the computation. Extensive simulation results show that the proposed framework significantly outperforms legacy channel contention mechanisms in terms of spectrum utilization while ensuring the ongoing transmissions unharmed.

Since the introduction of the 6 GHz spectrum, it has drawn widespread appeal among unlicensed radio access technologies (RATs), such as WiFi 6 and 5G New Radio-Unlicensed (NR-U). To appease this high demand and prevent the foreseeable saturation of the spectrum, efficient spectrum access strategies for competing WiFi 6 and 5G NR-U in the 6 GHz bands are essential. However, existing channel contention mechanisms of these RATs fail to capture the full availability of radio resources and consequently miss potential spectrum access opportunities. This is the first research on exploring these missed opportunities in the 6 GHz spectrum to capitalize on its full potential and prevent its imminent saturation. We propose a novel two-stage channel contention mechanism for the coexistence of WiFi 6 and 5G NR-U that facilitates the exploration of these missed spectrum access opportunities. Specifically, we formulate the probability of interference to the ongoing transmissions and enable the contending RATs to simultaneously access the channel by incorporating this probability. Extensive simulation results show that the proposed framework outperforms existing strategies in terms of spectrum utilization while maintaining interference-free coexistence of WiFi 6 and 5G NR-U.

The demand for radio resources, especially in the mid-band (i.e., 1-6 GHz) spectrum, is persistently increasing in wireless communications. Cognitive radio (CR) has emerged as a promising technology for addressing this increasing demand for the mid-band spectrum by enabling secondary users (SUs) to utilize the available spectrum opportunistically. This research, however, shows that more spectrum can be opportunistically accessed in the spatial domain by exploiting the frequency division duplexing (FDD) feature of cellular-based radio access technologies (RATs) in the mid-band spectrum, which remains undiscovered by existing opportunistic spectrum access techniques. This paper proposes a novel dynamic multi-channel spectrum access framework, employing actor-critic deep reinforcement learning (DRL), that leverages the FDD feature to explore these missed spectrum opportunities in CR networks. Extensive simulation results show that the proposed framework significantly outperforms FDD feature-unaware opportunistic spectrum access in terms of overall spectrum utilization.

Channel Rendezvous is a prerequisite and vital operation for two secondary users (SUs) to establish data communications in cognitive radio networks (CRNs). Channel hopping is a widely used method that can ensure two SUs meet on a common available channel within finite hops by following particularly designed hopping sequences. Most existing channel-hopping schemes are based on omnidirectional antennas. However, in a dense primary network, SUs with omnidirectional antennas can only use those channels that have no nearby PUs staying on. Such a limited number of available channels often leads to rendezvous failures. In this paper, we consider the utilization of directional antennas in the blind rendezvous process since more channels can be used due to the reduced interfering range. A novel joint design of sector hopping (beamforming) and channel hopping is proposed to guarantee the rendezvous. Furthermore, we identify a unique trade-off problem regarding the sector angle in these circumstances and derive an optimal solution that can adapt to different network conditions. Extensive simulation results demonstrate that the proposed framework significantly outperforms existing omnidirectional antenna-based rendezvous schemes under various dense primary networks.

Delay/disruption-tolerant networking (DTN) is a networking technology conceived to manage opportunistic connections with no consistent end-to-end link connectivity which is common in both terrestrial and space communication environments. DTN is recognized as a baseline technology for implementing deep-space networks. Considered as the primary transport protocol of DTN in space, Licklider transmission protocol (LTP) is expected to provide reliable data delivery service in a challenging networking environment regardless of presence of random link disruptions and/or extremely long propagation delays. The National Aeronautics and Space Administration (NASA) has implemented the use of DTN protocols on the International Space Station (ISS) for data delivery to the earth ground station. However, little work has been done in studying the performance of LTP for reliable data/file delivery in such a communication environment, especially in presence of link disruption. There is a lack of a solid performance evaluation of LTP for its use in the space station communications. In this paper, an analytical framework is presented to evaluate the performance of LTP for reliable file delivery between the space station and the ground stations with a focus on the effect of link disruption, which may occur either over the downlink or over the uplink. The effect of data loss due to channel error is also integrated. Realistic data block transmission experiments using a PC-based experimental infrastructure are conducted to validate the analytical models.

Deep neural networks have been widely used in remote sensing image segmentation. Nowadays, artificial intelligence methods are increasingly applied to remote sensing feature classification. Although convolutional neural networks (CNNs) are widely used for image segmentation tasks, their global feature extraction with increasing image samples is insufficient. Furthermore, transformer is now being focused on computer vision. However, although transformer can capture the global information of remote sensing images, it cannot adequately model the detailed information of image changes. To comprehensively compensate for the defects of CNNs and the transformer network in feature extraction, this study proposes a semantic segmentation network with multifeature fusion (SWINT-RESNet). This network combines the transformer-extracted global and local features and those of CNNs to improve the accuracy of remote sensing image segmentation. The experiments show that the segmentation performance of SWINT-RESNet is superior for both small and medium sample remote sensing image datasets.

Pipeline monitoring is of the essence for nowadays oil and natural gas delivery. Wireless Sensor Network (WSN) is the best candidate due to its low cost, ad-hoc feature, and ease of maintenance. However, there are quite limited WSNs that are particularly designed for long pipeline monitoring. Meanwhile, directly applying existing protocols may cause insufficient use of these WSNs and downgraded performance, especially on the lifetime of the network, which is a crucial metric for pipeline monitoring. Some efforts for lifetime extension do not fully utilize the features of pipeline or has some impractical assumptions when applying to pipeline scenarios. In this paper, we fully consider the practical factors and unique features of pipeline and propose a joint design of deployment and routing for such typed networks. In our design, a novel sensor deployment and a corresponding load balancing routing protocol are derived in terms of the maximized lifetime. The design considers the node damage, redundant data generated from the same event, and energy holes caused by dead nodes. Extensive simulation results validate our optimization and demonstrate our design can significantly improve the lifetime of the network and enjoy less overhead than the existing work. The simulation platform we used the MATLAB platform.

In the situation of an epidemic outbreak, a contact tracing tool is preferred to alert the infection status of daily encountered people. Since we are in the era that smartphone is carried everywhere and embedded with Bluetooth technology, a Bluetooth-based mobile app is proposed in this paper for advanced contact tracing. The proposed app can not only trace the infectious people contacted with the user but also label the danger level by scanning the proximity and lingering time for each case. It is simple yet efficient to apply as it does not employ any new Bluetooth protocol but only requires basic inputs that are acquirable from any smartphone with Bluetooth 2.0 and above. This application is built using service-oriented architecture which helps mobile devices to communicate with a data collection server as well as each other. The collected data will be shown in a web application and used to further study the propagation characteristics of new infectious viruses. It also comprises a daily survey that users answer, and which will be used by health officials for early prognosis. The app is currently tested campus-wide and showed salient features in terms of scalability, mobility, and sensing inaccuracy-proof, which has the potential to be applied in larger populations with more complicated scenarios.

Knowing the infection status of surrounding people can be a huge advantage for both self-protection and spreading control in an epidemic outbreak or a flu season. Recently, Bluetooth-based mobile apps have been implemented to perform the contacting tracking. However, self-status estimation and tracking are of the same importance yet less investigated. Unfortunately, existing apps cannot enable users to establish the necessary relationship between others' infection status and their own status. Meanwhile, traditional infection models are either used for statistics in the general population or have strong constraints that cannot be applied for such usage. In this paper, we propose BASE, a Bluetooth App-based Self-Estimated infection model, which can be integrated with this kind of app to calculate individual user's own infection probability. BASE only requires basic inputs that are acquirable from any smartphone with Bluetooth 2.0 and above. More importantly, BASE can work under practical scenarios in terms of scalability, mobility, and sensing inaccuracy. Furthermore, a learning model is integrated to calibrate the model by studying the propagation characteristics of heterogeneous diseases. The merits of BASE are proved theoretically and validated against extensive simulations. To the best of our knowledge, this is the first work that investigates the individual's infection model based upon Bluetooth neighbor discovery techniques.

In cognitive radio (CR) networks, rendezvous is when two secondary users tune to the same frequency channel simultaneously so that they can communicate with each other. Reducing the rendezvous delay, a.k.a the time to rendezvous (TTR), has been a highly focused topic for research. Many existing papers have tried to reduce the TTR between a pair of secondary users (SUs). To the best of our knowledge, no paper has previously considered the multi-destination rendezvous issue where a SU sender has different packets in its buffer for multiple destinations. Those who approached a similar scenario relied on a common control channel or the existence of multiple radios. In this research, we consider blind rendezvous using a single radio. We propose a new rendezvous protocol to handle the multiple destination scenario to decrease the overall TTR and increase the throughput, thus enhancing the overall performance of the CR network. Extensive simulations are carried out to demonstrate the performance of the proposed multi-destination rendezvous protocol.

With the rapid popularization of large data stream mobile applications, wireless local area networks (WLANs) have been a top choice for mobile users (MUs), because of the high data rate and low monetary cost. However, the battery life of mobile devices, which is the most concerned feature of MUs, may suffer from WLAN management services, such as mobility management and load balancing services. Unfortunately, few existing WLAN systems take into account both the energy efficiency of mobile devices and the performance of management services. Even worse, to improve the performance of WLAN management services, various existing management mechanisms sacrifice mobile devices' energy. In this paper, we propose BELL, a novel WLAN system that provides two energy-efficient management services for its associated MUs by reproducing and scheduling the beacons broadcast from access points (APs). We name them BELL- handoff and BELL-2M services. We have implemented the proposed BELL-handoff using commercial Wi-Fi adapters. The experimental results reveal that BELL-handoff significantly decreases both mobile devices' energy consumption and latency during handoffs, compared with the commercial WLAN mobility management service. Furthermore, we conduct extensive simulations to evaluate APs' load and mobile devices' battery life within a large-scale deployment of BELL. Simulation results demonstrate that BELL not only balances the load among APs, but also prolongs the battery life of mobile devices.

Device to device (D2D) communication is essential in Internet of things (IoT). Cognitive radio (CR)-enabled device is a promising technique to address D2D communications. Among all the functions supported in IoT, priority-based spectrum access is less investigated yet urgently desired in IoT. An important operation to achieve this capacity is channel hopping (CH) based rendezvous which allows two CR users to meet each other on a common available channel. Unfortunately, existing CH methods cannot help CR users achieve priority-based spectrum access due to various shortcomings. In this paper, we propose PCH, a priority-based spectrum access protocol for cognitive D2D, which can be integrated with any existing CH algorithm. PCH can support priority transmissions with a significantly reduced CH delay, as compared with non-priority transmissions. More importantly, PCH can work under practical scenarios such as the D2D both with priority packets, the D2D handoff, and the overhead/energy constraint IoT. The merits of PCH are proved theoretically and validated against extensive simulations. To the best of our knowledge, this is the first work that investigates priority communications in cognitive IoT.

Ideally, users in cognitive radio networks (CRNs) are capable of sensing and exploiting any potential transmission opportunities in the available spectrum band ranging from 30 KHz to 300 GHz. With the multiple-diverse-band spectrum, the network can provide more radio resources and capacity to a large number of CR users. However, the multiband scenario (e.g., TV band + 2/3G band + 4/5G band) also introduces significant challenges in channel rendezvous, a fundamental operation for users in CRNs to set up their communication link on a common channel. Existing studies on channel rendezvous suffer from unacceptable long delay and high energy consumption when applied to such scenarios. In this paper, we propose a two-dimensional heterogeneous rendezvous (2D-HR) protocol which can support multi-wideband CRNs (MWB-CRNs) with a significantly reduced rendezvous delay and energy consumption for various rendezvous scenarios, such as the pair-wise rendezvous, any-wise rendezvous, and multi-wise rendezvous. The proposed design also performs better than existing efforts even when dealing with traditional single-band rendezvous. The merits of 2D-HR are proved theoretically and validated against extensive simulations. To the best of our knowledge, this is the first work that addresses heterogeneous rendezvous in MWB-CRNs.

In multi-channel cognitive radio ad hoc networks (CRAHNs), packet fragmentation is impacted by new factors besides those in traditional wireless networks due to the unique CR functions. For example, spectrum handoff is the technique for a secondary user (SU) to continue its transmission when a primary user (PU) reoccupies its current transmitting channel. Then, a short frame is less likely to be affected by PU activities, which leads to a lower probability of retransmission. However, with the same header size, a long frame can convey more data than a short frame. In addition, the optimal fragmentation in terms of maximizing the throughput is also related to the spectrum handoff delay, node mobility, and the original packet size of the SU. More importantly, all these factors may vary with time and location, which makes this issue extremely challenging. In this paper, by mathematically modeling these impacts and dynamically mining the related parameters, we propose a self-adaptive protocol guiding the SU to derive the up-to-date optimal packet fragmentation. The proposed protocol is based on practical assumptions and taking other necessary CR functions into account such as spectrum sensing, channel hopping, and spectrum handoff. Simulation results validate our probabilistic model and the optimality of the fragmentation we derived. To the best of our knowledge, this is the first practical fragmentation protocol for multi-channel CRAHNs.

Cognitive radio (CR) technology is a promising solution to the spectrum scarcity problem. Due to the spectrum varying nature of CR networks, unlicensed users are required to perform channel hopping to realize blind rendezvous. However, blind rendezvous can easily cause deadlock in the network. Moreover, due to the nature of blind rendezvous, a deadlock cannot be detected by either the suffering users or other users. Consequently, a deadlock will eventually cause the whole network stuck and prohibit the network throughput. In this paper, the challenge of deadlock-free blind rendezvous in CR networks is addressed for the first time. By analyzing the deadlock issues in both two-user and multi-user scenarios, we propose a novel MAC protocol with an optimal contention window size which can avoid deadlock and provide high network throughput. In addition, we also propose a probabilistic model for analyzing the network performance with our MAC. Simulation results validate our analytical model and demonstrate that our proposed protocol outperforms other possible attempts.

Without a common control channel in cognitive radio ad hoc networks (CRAHNs), two secondary users have to first hop on a common available channel before setting up their communication link. Existing papers on this blind rendezvous process mainly focus on the sequence design of channel hopping but do not consider the selection of available channels. Their time to rendezvous (TTR) and operation complexity increase with the number of available channels, which is against the concept that cognitive radios should perform better when there are more unused channels in primary networks. Thus, a new blind rendezvous design that can address this paradoxical issue is desirable. In this paper, we propose a joint design of channel selection and channel hopping for guaranteed blind rendezvous. For the first time, the TTR is significantly reduced to O(1) with a low operation requirement. An analytical model of TTR is also proposed and validated against the simulation. More importantly, under our proposed protocol, TTR decreases with the increasing number of available channels in the network. This is a very attractive feature in spectrum-under-utilized scenarios which has not been achieved by any existing CRAHN rendezvous work.

In cognitive radio networks (CRNs), two users have to rendezvous on a common available channel before communications. Most existing rendezvous papers focus on the channel-hopping (CH) sequence design. However, rendezvous may suffer from the handshake failure on the rendezvous channel, especially in unsynchronized-slot scenarios. In this paper, the challenge of slot-asynchronous rendezvous in CRNs is addressed for the first time. A protocol aiming to improve the handshake performance during the CH process is proposed. By analyzing the potential factors leading to the handshake failure, we design a novel MAC protocol with an optimal size of a time slot which can mitigate the effects of these factors and provide the shortest time for rendezvous. In addition, we also propose a probabilistic model for estimating the average rendezvous time under different CRNs. Simulation results validate our analytical model and demonstrate that our proposed protocol can achieve the rendezvous time close to the theoretical value under slot-asynchronous scenarios.

In cognitive radio ad-hoc networks, two users rendezvous on a common available channel to realize communications. Most existing rendezvous papers focus on success-guaranteed channel-hopping sequence design. However, the theoretical rendezvous successful rate may suffer from the available channel status changing, collisions on channels, congestion at users, and target users unavailability in practical scenarios. Thus, a practical rendezvous framework that can address these issues is highly demanded. In this paper, we develop analytical models for each possible factor which may influence the performance of rendezvous. Then, based on the analysis of each factor, we propose corresponding schemes and integrate them into a self-adaptive protocol which can adjust its reaction and optimize system parameters to adapt to the dynamic network. Simulation results demonstrate that our proposed protocol gains better performance in terms of true rendezvous successful rate, short rendezvous delay, and low congestion. To the best of our knowledge, this is the first rendezvous protocol that addresses practical issues in realistic communication scenarios in cognitive radio networks.

Article Free Access Share on Minimization of chip size and power consumption of high-speed VLSI buffers Authors: D. Zhou The Department of Electrical Engineering, UNCC, Charlotte, NC The Department of Electrical Engineering, UNCC, Charlotte, NCView Profile , X. Y. Liu The Department of Electrical Engineering, UNCC, Charlotte, NC The Department of Electrical Engineering, UNCC, Charlotte, NCView Profile Authors Info & Claims ISPD '97: Proceedings of the 1997 international symposium on Physical designApril 1997 Pages 186–191https://doi.org/10.1145/267665.267711Published:01 April 1997Publication History 8citation419DownloadsMetricsTotal Citations8Total Downloads419Last 12 Months13Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF