Extended Data Delivery Time Research Articles

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.

Spectrum handoff analysis for multiple secondary users in cognitive radio networks

<p>The cognitive radio network permits secondary users to reach unused spectrum of primary users. In this paper, a mixed preemptive/non-preemptive resume priority M/G/1 queuing model is proposed for characterizing multiple handoff delay and to minimize the extended data delivery time of secondary users that has experienced multiple spectrum handoff during its transmission. The proposed queuing model supports delay-sensitive secondary user applications. The secondary users’ traffic is classified into two priority classes, the highest priority class for delay sensitive services and the lowest priority class for delay insensitive services. Furthermore, the proposed model assigns higher priority for the interrupted secondary users over uninterrupted secondary users for each class of secondary users in order to minimize the handoff delays for secondary users that experience multiple interruptions. Analytical formulas for the average extended data delivery time are derived for two different proactive spectrum handoff strategies (always stay and always change strategies) for both classes of secondary users. Simulation of proposed system model was performed to validate the analytical results and a good agreement was obtained. The performance of the suggested model is assessed and compared with other spectrum handoff models. Numerical results illustrate that the proposed system model outperforms existing models and can reduce the extended data delivery time for the secondary users.</p>

Hybrid Spectrum Handoff Scheme of Imperfect Sensing in Cognitive Radio Networks

Background: In the actual cognitive radio network, there exist the imperfect sensing such as false alarm and missed detection which can lead to the inaccurate spectrum handoff and cause more uncertain problems. Meanwhile, the predetermined target channel has high risk of being unavailable in the proactive-decision spectrum handoff scheme. Objective: To solve the problem that the state of the predetermined target channel is updated in the proactive-decision spectrum handoff scheme, we present a novel hybrid spectrum handoff scheme based on Preemptive Resume Priority (PRP) M/G/m queuing network model in this paper. Methods: The proposed scheme combines the advantages of proactive-decision spectrum handoff and reactive-decision spectrum handoff, and performs the spectrum sensing during the waiting time of the cognitive user on the target channel. On this basis, we consider the influence of multiple cognitive users, multiple authorization channels, multiple spectrum handoffs and other factors on the spectrum handoff delay of cognitive user. Then, the detailed analysis and derivations of cognitive user’s extended data delivery time are conducted. Furthermore, the effect of imperfect spectrum sensing on the spectrum handoff performance of cognitive users is discussed. Results: Compared with traditional spectrum handoff schemes, numerical results show that the extended data delivery time of the proposed scheme is smaller, and the performance of spectrum handoff is further improved. In addition, the performance of the proposed scheme is less affected by the probability of false alarm and missed detection with frequent channel states variations. Simulation results are given to validate the analytical results. Conclusion: The hybrid spectrum handoff scheme provide better performance on the spectrum sharing between primary users and cognitive users in cognitive radio network under imperfect sensing condition.

Spectrum Handoff based on Imperfect Channel State Prediction Probabilities with Collision Reduction in Cognitive Radio Ad Hoc Networks.

The spectrum handoff is highly critical as well as challenging in a cognitive radio ad hoc network (CRAHN) due to lack of coordination among secondary users (SUs), which leads to collisions among the SUs and consequently affects the performance of the network in terms of spectrum utilization and throughput. The target channel selection mechanism as part of handoff process can play an enormously significant role in minimizing the collisions among the SUs and improving the performance of a cognitive radio network (CRN). In this paper, an enhanced target channel selection scheme based on imperfect channel state prediction is proposed for the spectrum handoff among the SUs in a CRAHN. The proposed scheme includes an improved frame structure that increases coordination among the SUs in the ad hoc environment and helps in organizing the SUs according to the shortest job first principle during channel access. Unlike the existing prediction-based spectrum handoff techniques, the proposed scheme takes into account the accuracy of channel state prediction; the SUs affected due to false prediction are compensated by allowing them to contend for channel access within the same transmission cycle and thus enabling them to achieve higher throughput. The proposed scheme has been compared with the contemporary spectrum handoff schemes and the results have demonstrated substantial improvement in throughput and extended data delivery time by virtue of the reduced number of collisions.

Analysis of Efficient Spectrum Handoff in a Multi-Class Hybrid Spectrum Access Cognitive Radio Network Using Markov Modelling.

Cognitive radio networks (CRNs) rely on sensing of the licensed spectrum of a primary network to dynamically ascertain underutilized portion of the spectrum, thus affording additional communication opportunities. In a CRN, a single homogeneous spectrum access, such as interweave only deprives the secondary users (SUs) of channel access during handoff, particularly at high primary network traffic. Therefore, providing quality-of-service (QoS) to multi-class SUs with diverse delay requirements during handoff becomes a challenging task. In this paper, we have evolved a Markov-based analytical model to ascertain the gain in non-switching spectrum handoff scheme for multi-class SUs employing hybrid interweave-underlay spectrum access strategy. To satisfy the QoS requirements of the delay-sensitive traffic, we have analyzed the impact of hybrid spectrum access scheme for prioritized multi-class SUs traffic. The results show substantial improvement in spectrum utilization, average system throughput and extended data delivery time compared to conventional CRN using interweave only spectrum access. This demonstrates the suitability of the proposed scheme towards meeting QoS requirements of the delay-sensitive SU traffic while improving the overall performance for delay-tolerant SU traffic as well.

An optimized general target channel sequence for prioritized cognitive radio networks

Cognitive radio networks serve different secondary user applications which have distinct delay requirements. In order to better support the delay-sensitive applications, we consider secondary user traffic to be classified into M prioritized classes based on delay requirements. The priority of a secondary user increases within the same class after each interruption to reduce the cumulative handoff delay. A mixed preemptive/non-preemptive resume priority M/G/1 queueing model is assumed to analyze multiple spectrum handoffs. Closed form expressions are derived for both the extended data delivery time and dropping probability for each secondary user class. The analysis assumes a general target channel sequence, where a secondary user can select either to stay at his current channel or change it after each interruption. This general target channel sequence is optimized using a genetic algorithm in order to minimize the average extended data delivery time of all secondary user classes. Numerical results show that the proposed interruption-based priority mechanism outperforms the existing priority mechanisms in terms of average handoff delay and extended data delivery time in case of changing the target channel while preserves the extended data delivery time in case of always stay. Moreover, the optimized general target channel sequence gives better performance compared to the target channel sequences mentioned in the IEEE 802.22 wireless regional area networks standard for different network cases.

Reactive spectrum handoff combined with random target channel selection in cognitive radio networks with prioritized secondary users

Cognitive radio aims at improving spectrum utilization by allowing secondary users to access primary user’s spectrum. The delay time of secondary users due to multiple interruptions from primary users is considered a crucial issue. In this work, to reduce secondary user delay time, we propose a mixed preemptive/non-preemptive resume priority model where secondary user priority increases with each interruption by the primary user. We consider reactive spectrum handoff combined with random target channel selection for the case of all-busy channels. We derive closed form expressions of the average cumulative delay time and the extended data delivery time for each secondary user class. Numerical results show that the proposed approach reduces the secondary user delay time per class compared to other models in case of light loaded networks.

A New Probabilistic Target Channel Selection Approach for Load Balancing in Cognitive Radio Networks

Cognitive radio is a technology targeting better utilization for the available frequency bands by allowing the unlicensed secondary users (SUs) to access the licensed frequency bands of the primary users (PUs). The SU vacates the channel at the presence of the PU and selects a target channel reactively or proactively to complete his interrupted transmission. Target channel sequence order can greatly affect the performance of the network in terms of delay, capacity, and utilization. The probabilistic sequence target channel selection approach was shown to distribute the load smoothly among the available channels resulting in good load balancing characteristics and increasing network capacity and stability for an appropriate distribution function. In this paper, a new proactive probabilistic sequence approach to determine the target channel for the interrupted SUs is proposed to achieve load balancing. The pre-emptive resume priority M/M/1 queueing network model is used to analyse the proposed approach to evaluate the latency and load balancing performance. Moreover, a new quantitative performance measure for balancing is introduced. The proposed approach is compared to other alternative spectrum handoff strategies and numerical results show the advantage of the proposed probabilistic sequence approach by improving balancing and channel capacity. Moreover, the extended data delivery time is improved at low network loads.

A novel hybrid priority discipline for multi-class secondary users in cognitive radio networks

Recently, service differentiation in cognitive radio networks is an important issue. Delay-sensitive traffic such as VoIP transmission is given a higher priority over delay-insensitive traffic such as data transmission. Modeling such situation using classical preemption or non-preemption priority service disciplines may result in a severe degradation of the QoS for a particular class. To address this problem, we propose a hybrid service discipline at which low priority secondary users are no longer preempted by high priority secondary users when their number of interruptions reaches a certain threshold value. We carefully design this novel service discipline taking into account that the arrival of a primary user always preempts any secondary user ongoing transmission. Analytical formulas are derived for the extended data delivery time, the overall system time and the dropping probability for each class. Based on a set of numerical results presented for a 2-class network, it is shown that adjusting the threshold value according to the performance metric of interest provides a promising performance.

An Optimized Hybrid Approach for Spectrum Handoff in Cognitive Radio Networks With Non-Identical Channels

Cognitive radio (CR) is a technology that aims to enhance the use of the underutilized spectrum. Spectrum handoff plays this role by allowing the unlicensed secondary users (SUs) to use the licensed frequency bands of the primary users (PUs). Moreover, it helps the SU to vacate the channel at the presence of the PU and find a suitable channel for the interrupted SU to continue his unfinished transmission. In this paper, an analytical model for the general case of non-identical channels in CR networks is introduced for both fixed and probabilistic sequence approaches for target channel selection. Moreover, a new balancing model is suggested to generate the probabilistic sequence. Both the fixed and probabilistic sequence approaches are optimized using the meta-heuristic methods of particle swarm and genetic algorithm in the seek of finding an optimal approach to minimize the extended data delivery time of the SUs. The results are based on the pre-emptive resume priority M/M/1 queueing network model and are shown for different network cases. Based on the optimization results, a fast hybrid approach is proposed and found to achieve near optimal solution.

Spectrum handoff model based on preemptive queuing theory in cognitive radio networks

Cognitive radio can significantly improve spectrum efficiency by temporarily sharing under-utilized licensed frequency with primary users. Its spectrum management framework consists of four parts: spectrum sensing, spectrum decision, spectrum sharing and spectrum handoff. The last part is what we focus on in this paper. Spectrum handoff, which aims at guaranteeing requirement for service of secondary users and shortening time delay produced by interruption from primary users, is an important functionality of cognitive radio networks. For solving the problem of optimizing the extended data delivery time, a spectrum handoff model is proposed based on the preemptive resume priority M/G/m queuing theory. In order to minimize the extended data delivery time, the queuing method with mixed queuing and parallel service is adopted. In this model, each channel has its own high-priority queue and there is only one low-priority queue for all secondary users. The primary and secondary users respectively enter into the high-priority and low-priority queue to establish corresponding primary connections and secondary connections and execute corresponding data transmission. On the above basis, secondary users’ channel usage behaviors are thoroughly analyzed in the cases of multiple secondary users, multiple licensed channels and multiple spectrum handoffs. In this process, when multiple interruptions occur, the secondary user will stay on the current channel and suspend data transmission until primary users finish their data transmission, otherwise the secondary user will switch from the current channel to the predetermined target channel to resume his unfinished data transmission. The target channel is sequentially obtained from the target channel sequence, which is determined by channel parameter estimation algorithm. Based on the analysis of channel usage behaviors for secondary users, the total time delay caused by spectrum handoffs within the whole data transmission process is derived first. The total time delay can be deduced from two scenarios. One is that the target channel is the current channel. For this reason, the total time delay equals transmission time of primary users in high-priority queue. Obviously, the other is that the target channel is not the current channel. Thus, the total time delay equals the sum of transmission times of primary users in high-priority and secondary users ahead in low-priority. In addition, appearance of new primary users should also be considered in the data transmission process. Then, expressions of the extended data delivery time in two different cases (i. e. always-staying strategy and always-changing strategy) are respectively derived. Furthermore, the adaptive spectrum handoff strategy is finally discussed, which is to choose the optimal scheme from always-staying and always-changing strategy when a spectrum handoff happens. Simulation results verify that this model can not only describe handoff behaviors of secondary users more perfectly, but also can make the transmission time delay smaller and make the extended data delivery time shorter than the existing spectrum handoff model. Especially, with the increase of service intensity of primary users, the advantages of the proposed spectrum handoff model are more outstanding. In addition, the allowable secondary user service intensity is improved and the receptive number of secondary user is increased in cognitive radio networks. All in all, the proposed spectrum handoff model improves the performance of spectrum handoff, increases the capacity of cognitive radio networks and optimally realizes spectrum sharing between secondary users and primary users.

Research on the Lifetime Estimation of Secondary Connections Using the PRP M/G/1 Queuing Network Model

Allocated Spectrum band has always been a limited resource; being later a more challenging issue due to the growth of user demands. The past decade is marked by important changes in spectrum access through especially cognitive radio technology. Here, spectrum access issue can be studied in all the different aspects of cognitive capabilities. This paper focuses on spectrum handoff in spectrum mobility. We will then study secondary connections behaviors after multiple interruptions providing from multiple secondary connections. In the IEEE 802.22 standards [, two Spectrum Handoff Sequences have been defined to characterize Secondary Connections behaviors after each Primary Connections interruption. These sequences are known as always-leaving and always-staying sequences. A recent analysis uses the extended data delivery time metric to analyze these Spectrum Handoff Sequences. It shows the exponential value of connections service time in the first sequence (always-leaving sequence) and in the other (always-staying sequence), the lack of fairness due to the acquisition of channels low-priority queue by the ongoing secondary connection (i.e. the secondary connection actually being served in the low-priority queue). Weve also noticed that the Extended Data Delivery Time is a good but limited metric because of the lack of prevision, which is a quality needed in cognitive radio networks, especially when implementing spectrum handoff sequences. Our present study aims to analyze these limitations. In what follows, we use the PRP M/G/1 queuing model in cognitive radio network to evaluate latency-sensitive traffic of Secondary Connections through a novel performance metric that we name Lifetime of Secondary Connections.

Modeling and Analysis for Spectrum Handoffs in Cognitive Radio Networks

In this paper, we present an analytical framework to evaluate the latency performance of connection-based spectrum handoffs in cognitive radio (CR) networks. During the transmission period of a secondary connection, multiple interruptions from the primary users result in multiple spectrum handoffs and the need of predetermining a set of target channels for spectrum handoffs. To quantify the effects of channel obsolete issue on the target channel predetermination, we should consider the three key design features: 1) general service time distribution of the primary and secondary connections; 2) different operating channels in multiple handoffs; and 3) queuing delay due to channel contention from multiple secondary connections. To this end, we propose the preemptive resume priority (PRP) M/G/1 queuing network model to characterize the spectrum usage behaviors with all the three design features. This model aims to analyze the extended data delivery time of the secondary connections with proactively designed target channel sequences under various traffic arrival rates and service time distributions. These analytical results are applied to evaluate the latency performance of the connection-based spectrum handoff based on the target channel sequences mentioned in the IEEE 802.22 wireless regional area networks standard. Then, to reduce the extended data delivery time, a traffic-adaptive spectrum handoff is proposed, which changes the target channel sequence of spectrum handoffs based on traffic conditions. Compared to the existing target channel selection methods, this traffic-adaptive target channel selection approach can reduce the extended data transmission time by 35 percent, especially for the heavy traffic loads of the primary users.