Hybrid Spectrum Access Research Articles

Correction: Transient analysis of enhanced hybrid spectrum access for QoS provisioning in multi-class cognitive radio networks

Correction: Transient analysis of enhanced hybrid spectrum access for QoS provisioning in multi-class cognitive radio networks

Transient analysis of enhanced hybrid spectrum access for QoS provisioning in multi-class cognitive radio networks

Transient analysis of enhanced hybrid spectrum access for QoS provisioning in multi-class cognitive radio networks

Downlink resource allocation for NOMA-based hybrid spectrum access in cognitive network

To solve the contradiction between limited spectrum resources and increasing communication demand, this paper proposes a wireless resource allocation scheme based on the Deep Q Network (DQN) to allocate radio resources in a downlink multi-user cognitive radio (CR) network with slicing. Secondary users (SUs) are multiplexed using non-orthogonal multiple access (NOMA). The SUs use the hybrid spectrum access mode to improve the spectral efficiency (SE). Considering the demand for multiple services, the enhanced mobile broadband (eMBB) slice and ultrareliable low-latency communication (URLLC) slice were established. The proposed scheme can maximize the SE while ensuring Quality of Service (QoS) for the users. This study established a mapping relationship between resource allocation and the DQN algorithm in the CR-NOMA network. According to the signal-to-interference-plus-noise ratio (SINR) of the primary users (PUs), the proposed scheme can output the optimal channel selection and power allocation. The simulation results reveal that the proposed scheme can converge faster and obtain higher rewards compared with the Q-Learning scheme. Additionally, the proposed scheme has better SE than both the overlay and underlay only modes.

Enhancing Hybrid Spectrum Access in CR-IoT Networks: Reducing Sensing Time in Low SNR Environments

The current utilization of the licensed spectrum band is not optimal. the abundance of Internet of Things (IoT) gadgets could lead to congestion in the unlicensed spectrum band. A potential solution is to integrate cognitive radios into IoT devices, specifically by developing CR-IoT (cognitive-radio-enabled IoT) devices that leverage the hybrid spectrum access (HSA) technique to access the licensed spectrum band and employ energy detectors for spectrum sensing. While HSA can enable high data throughput for CR-IoT networks, environments with low signal-to-noise ratio (SNR) may experience reduced performance. Particularly, in low SNR environments with SNR values ranging from -20dB to -24dB, the high level of noise uncertainty can cause the energy detector to spend more time sensing, which results in a significant reduction in transmission time and overall throughput. In this study, a novel approach is presented to address the challenge of noise uncertainties on the energy detector by implementing an adaptive sensing threshold. The simulation outcomes reveal that the proposed technique can significantly improve the throughput in scenarios characterized by low signal-to-noise ratio (SNR), with a maximum enhancement of up to 28%. This innovative approach can pave the way for more robust and efficient energy detectors in the presence of noise uncertainties .

Design and Development of Hybrid Spectrum Access Technique for CR-IoT Network

The radio spectrum is an underutilized natural resource with significant untapped potential. The rapid proliferation of Internet of Things (IoT) devices is driving a dramatic increase in radio spectrum demand. These devices can utilize cognitive radio (CR) technology to access the bandwidth left unused by licensed spectrum users, also known as primary users (PUs), to meet end users spectrum requirements efficiently. However, because PUs are given priority, CR-enabled Internet of Things (CR-IoT) devices, also known as secondary users (SU), must frequently communicate with one another in an opportunistic manner or under stringent power constraints. This can complicate CR-IoT device communication, render it unstable, and restrict its throughput. This paper proposes a hybrid spectrum access algorithm that combines underlay and interweave spectrum access methods to address this issue. When a PU is detected, under the proposed scheme, CR-IoT devices utilize underlay spectrum access. In contrast, when no PU is detected, CR-IoT devices employ interweave spectrum access. In addition, a proposed iterative algorithm permits CR-IoT devices to adapt their sensing thresholds, and sensing time based on the Signal-to-Noise ratio (SNR) received from Pus to strike a balance between achievable throughput and fairness among PUs and CR-IoT devices in extremely noisy channel. Simulation results demonstrate that the throughput for CR-IoT devices increases by 28% in proposed scheme when compared to the conventional spectrum access schemes.

NOMA-Based Cooperative Relaying Transmission for the Industrial Internet of Things

With the continuous maturity of the fifth generation (5G) communications, industrial Internet of Things (IIoT) technology has been widely applied in fields such as smart factories. In smart factories, 5G-based production line monitoring can improve production efficiency and reduce costs, but there are problems with limited monitoring coverage and insufficient wireless spectrum resources, which restricts the application of IIoT in the construction of smart factories. In response to these problems, we propose a hybrid spectrum access mechanism based on Non-Orthogonal Multiple Access (NOMA) cooperative relaying transmission to improve the monitoring coverage and spectrum efficiency. As there are a large number of production lines that need to be monitored in smart factories, it is difficult to realize real-time monitoring of all production lines due to insufficient wireless resources. Therefore, we divide the production lines into high priority and low priority, and introduce cognitive radio technology to increase the number of monitoring production lines. In order to better describe the wireless fading channel environment in the factory, the two-wave with diffuse power (TWDP) channel is discussed to simulate the real factory environment and the outage probability of the secondary production line data transmission is derived in the proposed mechanism. Compared with the traditional mechanism, the proposed transmission mechanism can ensure the continuity of the secondary transmission, greatly reduce the outage probability of the secondary transmission, and improve the efficiency of the monitoring of the production lines.

A hybrid spectrum access approach for efficient channel allocation and power control in cognitive radio networks

SummaryRadio spectrum is the backbone for wireless communication. Many recent studies show that most of the available spectrum has already been allocated. Cognitive radio (CR) provides a new dimension in the field of wireless communication and is considered as a life line for the spectrum scarcity problem as seen all around the world nowadays. CR enables the use of dynamic spectrum access, where secondary users (SUs) or unlicensed users are allowed to opportunistically use the spectrum when it is not being used by the primary users (PUs) or licensed users. Medium Access Control (MAC) protocols use the sensing capability and the primary users behavior to generate the transmission opportunities for SUs. This article proposes two Markov based hybrid access methods namely Hybrid‐P1 and Hybrid‐P2, where a secondary user (SU) dynamically decides it's transmission mode between overlay and underlay depending upon the primary users's (PU's) past and present behavior. Analytical results based on the Markov chain concept are very encouraging and verified through OMNeT++ simulator. This work also analyses the performance of overlay only and underlay only methods, which are well known data transmission techniques in the cognitive radio networks (CRNs). Simulation results show the 47% and 59% performance improvement in Hybrid‐P1 access method, when compared to the overlay only and underlay only access methods respectively. Furthermore simulation results also show the 54% and 65% performance improvement in Hybrid‐P2 access method, when compared to the overlay only and underlay only access methods respectively.

HSA-SPC: Hybrid Spectrum Access with Spectrum Prediction and Cooperation for Performance Enhancement of Multiuser Cognitive Radio Network

The spectrum sensing (SS) is employed to identify the status of licensed channel in the cognitive radio/user (CR/CU). Arbitrarily choosing the licensed channel for sensing in high traffic intensity network results into reduced throughput of cognitive user due to wait state problem in interweave mode. However, the wait state problem is overcome with hybrid spectrum access, resulting into improvement in throughput of CU. In addition, the sensing decisions without cooperation increases the sensing error and affect the sensing performance of CU resulting into reduction in throughput of CU. In this paper, we have proposed new approach that is Hybrid Spectrum Access with Spectrum Prediction and Cooperation (HSA-SPC) of cognitive users in which we have collectively employed spectrum prediction, cooperation and hybrid spectrum access to improve the sensing performance and throughput of CU. Further, for the proposed approach we have considered a new frame structure in multiuser environment and derived the closed form expression for the throughput. In addition to this, we have also shown the computation of energy efficiency for our proposed approach. Further, with the help of simulation results, we have shown the improvement in CU throughput with our proposed approach over reported literature. Comparison of various approaches with the proposed method HSA-SPC is also illustrated.

Spectrum utilization efficiency in CRNs with hybrid spectrum access and channel reservation: A comprehensive analysis under prioritized traffic

The enhancement of spectrum utilization efficiency (SUE) is a critical objective in fifth generation networks-enabled Internet of Things (5G-IoT) for providing communication opportunities to plethora of 5G-IoT devices within the already scarce spectrum. Cognitive radio networks (CRNs) with interweave and underlay modes are foreseen to achieve this objective. The interweave mode is adequate for legacy CRNs, while the underlay mode is fitting for resource-constrained CRNs. As 5G-IoT is rapidly evolving into heterogeneous networks, CRNs enabled by hybrid underlay-interweave mode (H-mode) emerge to be the best option for SUE enhancement in 5G-IoT. In this paper, we comprehensively analyze the performance of H-mode enabled CRNs containing heterogeneous users by proposing two H-mode schemes, namely, primary user full priority (FP) and primary user partial priority (PP). The schemes consider secondary users (SUs) with high and low priorities. In FP, primary users (PUs) have absolute priority in channel access while in PP, SUs with certain attributes are immune from interruptions. Additionally, to accommodate interrupted users, a simple yet efficient channel reservation algorithm is proposed, which divides the given channels into reserved and unreserved bands. Using Markov chain modeling, expressions are derived for core SUE related performance metrics including service completion rate (SCR), blocking probability (BP), network serveability (NS), successful service completion probability (SSCP), handoff probability, and throughput, independently for PUs and all types of SUs. Performance of the proposed schemes is analyzed under varying channel failure rates and network traffic loads. Efficacy of the proposed schemes is shown through analytical and simulation results against state-of-the-art. Improvements of up to 67% in BP and 83% in cost efficiency are recorded as compared to the state-of-the-art. Likewise, up to 10% and 84% difference in PUs’ and SUs’ SSCP, respectively, and up to 17% and 93% difference in PUs’ and SUs’ SCR, respectively, are noted. Similarly, up to 85% performance difference in NS is recorded. Moreover, up to 35% improvement in throughput in H-mode is witnessed. Lastly, handoff probability is found to be increased by 5%.

NOMA-Based Cognitive Spectrum Access for 5G-Enabled Internet of Things

With the rapid development of 5th generation (5G) communications, 5G-enabled Internet of Things (IoT) will provide high-speed and low-latency data transmissions as well as better communication coverage. 5G-enabled IoT can achieve efficient and reliable connections of massive nodes via the technical advantages of ultra-reliable low-latency communication (uRLLC), massive machine-type communication (mMTC) and enhanced mobile broadband (eMBB). However, the shortage of spectrum resources has become a bottleneck restricting the development of 5G-enabled IoT. Cognitive radio (CR) and non-orthogonal multiple access (NOMA) are emerging as promising spectrum sharing technologies to improve spectrum utilization. In this article, by integrating CR and NOMA, NOMA-based cognitive spectrum access is studied to improve the spectral efficiency of 5G-enabled IoT, by which the IoT may access the spectrum licensed to a primary user (PU) via NOMA. First, underlay, overlay and hybrid spectrum access modes based on NOMA are described, respectively, and two successive interference cancellation (SIC) schemes are proposed to guarantee the decoding performance of IoT and PU, respectively. Second, subcarrier aggregation-based NOMA and interference suppression-based NOMA decoding are presented to improve the utilization of discrete idle spectrum and decrease the impact of PU's interference on decoding, respectively. Third, grant-free NOMA and compressed sensing-based NOMA decoding are proposed to improve the performance of URLLC and mMTC, respectively. Fourth, cooperative NOMA is presented to improve the transmission performance of PU and IoT in fading channels. Finally, some open research works and challenges are discussed.

Hybrid spectrum access in a cognitive radio‐enabled cooperative device‐to‐device network

SummaryIn this paper, the performance of a co‐operative device‐to‐device (D2D) network is investigated. All the D2D users sense the cellular user (CU) spectrum and use it in hybrid mode: underlay and overlay. The expressions of throughput and outage are developed under the considered network scenario. An algorithm is proposed to optimize the sensing time to minimize the outage. The performance is investigated in terms of throughput and outage for several network parameters such as a number of D2D users, sensing time, signal‐to‐noise ratio (SNR), allowable interference threshold, and CU transmit power. Sensing time is optimized to minimize the outage. The interference threshold and target rate have a significant impact on network performance. The network has to suffer outage for lower values of allowable interference threshold and higher values of the target rate. The impact of channel fading on the network performance is also studied. A simulation model is developed in MATLAB on the basis of the analytical development of the considered network model.

Age of Information and Success Probability Analysis in Hybrid Spectrum Access-Based Massive Cognitive Radio Networks

In this paper, we investigate users’ performance under the hybrid spectrum access model in the massive cognitive radio network (CRN), where multiple primary users (PUs) and secondary users (SUs) transmit on the same channel simultaneously. SUs first detect the state of the channel via channel sensing and select an appropriate channel access scheme (either underlay or overlay) for their transmissions based on the outcome of the channel sensing. When at least one PU is active, SUs transmit under the underlay channel access scheme by employing the power control technique to ensure that the interference generated in the primary network is below the pre-defined interference threshold. In the absence of PU, SUs transmit with full transmit power under the overlay channel access scheme, thereby maximizing their throughput. Using the tool of stochastic geometry, we obtained tractable analyses for important metrics such as success probability, throughput, and the average age of information (AoI) in both primary and secondary networks, while capturing the interference between the two networks. The obtained analyses offer an efficient way to understand the metrics of AoI, throughput and success probability in the hybrid spectrum access-based CRN. We further compared users’ performance under the hybrid spectrum access scheme with performances under overlay and underlay spectrum access schemes. The outcome of the numerical simulations shows that the hybrid spectrum access scheme can significantly improve the performance of users in the network, while also capturing more key features of real-life systems.

Enhanced Spectrum Access for QoS Provisioning in Multi-Class Cognitive D2D Communication System

Integration of Device-to-Device (D2D) communication into the cellular network can greatly enhance the spectrum utilization as well as creating additional communication opportunities. D2D can be combined with cognitive radio to further enhance spectrum utilization and cellular network performance. Unlike the traditional D2D communication approach which employs only cellular spectrum, cognitive D2D can enable sensing and utilizing non-cellular spectrum opportunistically as well, thus allowing to offload cellular base station traffic to non-cellular spectrum such as WiFi, Bluetooth, or TV white-spaces. Cognitive D2D users (cDUs) must vacate channel for primary users and hand-off to another secondary channel which renders it quite challenging to meet Quality of Service (QoS) requirements of multi-class cDUs in the presence of higher primary network load. In this work, an enhanced hybrid spectrum access scheme has been developed based on non-switching spectrum hand-off for multi-class DUs, utilizing both interweave and hybrid interweave underlay spectrum access strategies. Further, lower priority cDUs with non-real-time traffic remains in the system and wait for channels to become available, rather than being dropped from the system due to lack of secondary channels. A Continuous-Time Markov Chain (CTMC) has been developed to analyze the performance of the proposed scheme. For comparison, several cases, ranging from the simple cellular network to complex cellular-cognitive-D2D with hybrid-spectrum-access, have been analyzed. The main focus of the analysis is to compare the efficacy of enhanced hybrid spectrum access scheme with individual interweave and hybrid interweave underlay spectrum access strategies in terms of QoS provisioning for multi-class cDUs. The results depict improvement in throughput, spectrum utilization, and extended data delivery time for the proposed scheme and validate the suitability of the proposed scheme to meet QoS requirements for both delay-sensitive and delay-tolerant users of the multi-class cognitive D2D communication system.

Uplink Resource Allocation for NOMA-Based Hybrid Spectrum Access in 6G-Enabled Cognitive Internet of Things

Sixth generation (6G)-enabled Internet of Things (IoT) needs sufficient spectrum resources to provide spectrum access for massive IoT’s terminals. However, traditional orthogonal multiple access restricts the full use of limited spectrum resources. In this article, a nonorthogonal multiple access (NOMA)-based hybrid spectrum access scheme is proposed for 6G-enabled cognitive IoT (CIoT), where the CIoT may access both the idle and busy spectrum via NOMA regardless of the primary user’s (PU) state. The uplink resource allocations for the CIoT are optimized in the decoding-PU-last and decoding-PU-first schemes, respectively, which seek to maximize the average total transmission rate of CIoT while ensuring the minimum transmission rates for PU and each CIoT node. Then, a clustering NOMA-based CIoT is presented to decrease the interuser interference, where the nodes in each cluster use NOMA to transmit in the allocated subchannel. The simulation results have shown the performance advantages for the NOMA-based hybrid spectrum access and better rate guarantee for the clustering NOMA-based CIoT.

Energy-Efficient Resource Allocation for Cognitive Industrial Internet of Things With Wireless Energy Harvesting

Cognitive industrial Internet of Things (CIIoT) can extend available spectrum resources by accessing the spectrum licensed to primary user (PU) on the premise of not disturbing the PU's communications. However, additional spectrum sensing and long-time working may consume much energy of CIIoT. In this article, a CIIoT with wireless energy harvesting (WEH) is proposed to harvest the radio frequency energy of PU's signal, and energy-efficient resource allocations in different spectrum access modes are presented to maximize the average transmission rate of CIIoT while guaranteeing its energy saving requirements. The underlay and overlay spectrum access modes for CIIoT with WEH are described, respectively, in which the energy-efficient resource allocations are formulated as joint optimization problems that can be solved using the alternating direction optimization and water-filling algorithm. By combining underlay and overlay modes, a hybrid spectrum access mode is proposed to enable the CIIoT to access both idle and busy spectrum without limiting its transmission power at the absence of PU. Simulation results show that the CIIoT with WEH can consume less power to achieve larger transmission rate, and the hybrid mode outperforms the underlay and overlay modes in the aspects of transmission rate and energy saving.

Cognitive Radio Techniques for Utilizing the Primary L-Band Distance Measuring Equipment for Aeronautical Communications

The aeronautical communication has been switched from the congested very high frequency (VHF) band to occupy the L-band, namely, L-band digital aeronautical communication system type I (LDACSI). Critical navigation system in this band is the distance measurement equipment (DME). However, the DME channels provide a severe interference to onboard LDACSI receiver. In this paper, a cognitive radio (CR) network is proposed to allow efficient spectrum reuse with coexisting primary DME channels. In LDACSI-CR network, the proposed spectrum sensing technique is performed by using an adaptive threshold DME energy detector to achieve the best trade-off between the DME signal detection and false alarm. Moreover, dynamic spectrum access, namely, hybrid spectrum access (HSA) is newly introduced to enhance the LDACSI-CR throughput. Joint effect of HSA with different frame structures on the LDACSI throughput is proposed. Besides, optimal power allocation using genetic algorithm that maximizes the LDACSI-CR ergodic throughput for HSA with different frame structures is proposed. In this work, the closed form expression for the probability of DME detection, false alarm, detection error, the LDACSI throughput and data loss are derived. Simulation is performed and the results show the LDACSI throughput and the data loss for the proposed techniques. Besides, ergodic throughput maximization for HSA under constraints of the average LDACSI transmitted power and tolerable interference power on the DME signal is performed. Moreover, simulation results show that the proposed LDACSI-CR system performance provides lower bit error rate and less complexity compared to the previous work.

Maximum-Throughput Sidelink Resource Allocation for NR-V2X Networks With the Energy-Efficient CSI Transmission

New radio vehicle-to-everything (NR-V2X) is an emerging technology based on the 5G cellular mobile communication networks. In this paper, the sidelink (SL) resource allocation for NR-V2X in Mode 1 is considered, where 5G base station (gNB) schedules SL resources to be used by V2X users (VUs) based on the periodically reported channel state information (CSI). To reduce the overhead, an energy efficient power allocation scheme of CSI transmission is proposed using hybrid spectrum access technology. With the knowledge of CSI, SL resource allocation is modeled as a mixed binary integer nonlinear programming (MBINP). It is designed to maximize the sum throughput of NR-V2X networks among different subcarriers subject to the total available power and the minimal transmission rate. To achieve that, the original MBINP is decomposed into two sub-problems, namely, subcarrier assignment and power allocation. Firstly, the appropriate subcarriers are quickly obtained by averaging the power allocation. Secondly, an alternative optimization mechanism is proposed to the power allocation. Simulation results show that the proposed power allocation scheme of CSI transmission can obviously save the energy consumption, and the proposed suboptimal SL resource allocation algorithm achieves better performance than the compared methods with relatively low complexity.

Hierarchical and Hybrid: Mobility-Compatible Database-Assisted Framework for Dynamic Spectrum Access

The protection of primary user activities plays a vital part in dynamic spectrum access. There are currently two types of schemes. One is based on spectrum sensing and the other one relies on spectrum database. There exist many works surrounding the subject of spectrum sensing, which requires high sensing accuracy, and thus poses extra time cost. Nevertheless, the database-based access scheme is receiving an increasing amount of devotion, e.g., IEEE 802.11af for TV white space. In comparison to spectrum sensing, nodes only need to look up the spectrum maps provided by the database. In this paper, we study the practical issues of the above two schemes, and propose a hierarchical framework, which enables the hybrid spectrum access scheme. In this framework, we build relatively reliable clusters, and have cluster heads connect to the spectrum database to assist nodes in their clusters. As a result, nodes with poor or no connections to the database can benefit from spectrum maps as well. The process of retrieving spectrum maps is formalized as a Markov Decision Process. Moreover, mobility compatibility is provided. We illustrate how the evolution of our hierarchical structure is affected by mobile nodes. We also propose a feasible algorithm to maximize the benefits that can be obtained from the database under the mobile environment. We model a virtual database and conduct simulations to reveal certain performances of our framework.

A Hybrid Spectrum Access Strategy with Channel Bonding and Classified Secondary User Mechanism in Multichannel Cognitive Radio Networks.

Cognitive radio networks (CRNs) can improve spectrum utilization by allowing secondary users (SUs) to dynamically access channels unoccupied by primary users (PUs). The spectrum access strategy, as a point to enhance user performance, has received much attention. In this paper, we propose a hybrid access mode for network users in multichannel CRNs. For meeting different SU demands, SUs are classified as SU1s and SU2s. We further introduce a channel bonding scheme for high-priority (PU and SU1) user packets to enhance transmission efficiency. At the same time, we propose a hybrid spectrum access strategy for SU2 packets to improve their transmission stability. By establishing a Markov chain model, some important SU2 packets’ performance measures are derived. Furthermore, we display the comparison of hybrid, overlay and underlay modes by numerical results to analyze the advantages of different modes.

Hybrid spectrum access model using game theory approach for multi-channel heterogeneous mobile cognitive radio wireless sensor network

<p>An efficient spectrum access and medium access control (MAC) design is required to enable wireless sensor network (WSN) with cognitive Internet of Things (IoT) that enables presence of sensor network with existing wireless infrastructure. Designing spectral, energy efficient and fair spectrum access design for IoT in CR-WSN is challenging especially for heterogeneous mobile CR-WSN. Existing model induces high collision and energy overhead. As a result, they are not efficient in utilizing spectrum. To overcome the research issues, this paper proposes a hybrid spectrum access model (HSAM) for multi-channel heterogeneous mobile CR-WSN. Next it elaborates on an accurate feasible channel accessible likelihood estimation. Further, we present a game theory model for HSAM for existence of fine-grained Nash equilibrium. Experiments are conducted to evaluate the performance of HSAM-CRWSN over existing model. The outcome shows HSAM-CRWSN attains significant performance improvement over state-of-art technique in terms of energy efficiency, throughput, successful packet transmission and packet collision. The HSAM-CRWSN improves the overall spectrum efficiency of CR-WSN.</p><p><span style="font-size: small;"><br /></span></p>