Call Blocking Probability and Packet Delay in Cognitive Radio Networks

Cognitive radio networks (CRNs), which allow secondary users (SUs) to dynamically access a network without affecting the primary users (PUs), have been widely regarded as an effective approach to mitigate the shortage of spectrum resources and the inefficiency of spectrum utilization. However, the SUs suffer from frequent spectrum handoffs and transmission limitations. In this paper, considering the quality of service (QoS) requirements of PUs and SUs, we propose a novel dynamic flow-adaptive spectrum leasing with channel aggregation. Specifically, we design an adaptive leasing algorithm, which adaptively adjusts the portion of leased channels based on the number of ongoing and buffered PU flows. Furthermore, in the leased spectrum band, the SU flows with access priority employ dynamic spectrum access of channel aggregation, which enables one flow to occupy multiple channels for transmission in a dynamically changing environment. For performance evaluation, the continuous time Markov chain (CTMC) is developed to model our proposed strategy and conduct theoretical analyses. Numerical results demonstrate that the proposed strategy effectively improves the spectrum utilization and network capacity, while significantly reducing the forced termination probability and blocking probability of SU flows.

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Performance Analysis of Cognitive Radio Networks with a Two-Part Queue

The Open Electrical & Electronic Engineering Journal ◽

10.2174/1874129001509010238 ◽

2015 ◽

Vol 9 (1) ◽

pp. 238-246

Author(s):

Min Zhang ◽

Bin Li

Keyword(s):

Performance Measures ◽

Packet Loss ◽

Queue Length ◽

Blocking Probability ◽

Packet Delay ◽

Loss Ratio ◽

Call Blocking ◽

Packet Loss Ratio ◽

Call Blocking Probability ◽

Level Performance

In a cognitive radio network (CRN), a preempted secondary user (SU) is placed in a call level queue to wait for accessing another free channel. If the availability of channels is transparent to SUs, packets will be generated during their waiting time and the performance of the CRN will be influenced by which way to handle these packets. In this paper, the call level queue is departed into two parts, delay queue and discard queue. Here, an analytical model is developed to derive the formulas for both call level performance measures (i.e., call blocking probability) and packet level performance measures (i.e., packet delay, packet loss ratio and throughput). Numerical results show that theoretical models are consistent with simulation results. The major observations include (i) The performances of an SU degrade as the call arrival rate increases. (ii) With the increase of the delay queue length, the SU call blocking probability and packet delay increase, while the packet loss ratio and throughput decrease. (iii) Adopting different delay queue length causes a smaller effect on call blocking probability and throughput than on packet loss ratio and packet delay.

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Improved Buffer-Aided Multi-Hop Relaying with Reduced Outage and Packet Delay in Cognitive Radio Networks

Electronics ◽

10.3390/electronics8080895 ◽

2019 ◽

Vol 8 (8) ◽

pp. 895

Author(s):

Shakeel Alvi ◽

Riaz Hussain ◽

Qadeer Hasan ◽

Shahzad Malik

Keyword(s):

Cognitive Radio ◽

Outage Probability ◽

Cognitive Radio Networks ◽

Communication Systems ◽

Performance Metrics ◽

Packet Delay ◽

Radio Spectrum ◽

Radio Networks ◽

Cooperative Relaying ◽

End To End

Cognitive radio networks have emerged to exploit optimally the scarcely-available radio spectrum resources to enable evolving 5G wireless communication systems. These networks tend to cater to the ever-increasing demands of higher data rates, lower latencies and ubiquitous coverage. By using the buffer-aided cooperative relaying, a cognitive radio network can enhance both the spectral efficiency and the range of the network; although, this could incur additional end-to-end delays. To mitigate this possible limitation of the buffer-aided relaying in the underlay cognitive network, a virtual duplex multi-hop scheme, referred as buffer-aided multi-hop relaying, is proposed, which improves throughput and reduces end-to-end delays while keeping the outage probability to a minimum as well. This scheme simultaneously takes into account the inter-relay interference and the interference to the primary network. The proposed scheme is modeled as a Markov chain, and Monte Carlo simulations under various scenarios are conducted to evaluate several key performance metrics such as throughput, outage probability, and average packet delay. The results show that the proposed scheme outperforms many non-buffer-aided relaying schemes in terms of outage performance. When compared with other buffer-aided relaying schemes such as max-max, max-link, and buffer-aided relay selection with reduced packet delay, the proposed scheme demonstrated better interference mitigation without compromising the delay performance as well.

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Resource Allocation in Heterogeneous Buffered Cognitive Radio Networks

Wireless Communications and Mobile Computing ◽

10.1155/2017/7385627 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12

Author(s):

B. S. Awoyemi ◽

B. T. Maharaj ◽

A. S. Alfa

Keyword(s):

Resource Allocation ◽

Cognitive Radio ◽

Cognitive Radio Networks ◽

Blocking Probability ◽

Radio Networks ◽

Base Station ◽

Limiting Factor ◽

Efficient Resource ◽

Overall Performance ◽

Performance Results

Resources available for operation in cognitive radio networks (CRN) are generally limited, making it imperative for efficient resource allocation (RA) models to be designed for them. However, in most RA designs, a significant limiting factor to the RA’s productivity has hitherto been mostly ignored, the fact that different users or user categories do have different delay tolerance profiles. To address this, in this paper, an appropriate RA model for heterogeneous CRN with delay considerations is developed and analysed. In the model, the demands of users are first categorised and then, based on the distances of users from the controlling secondary user base station and with the assumption that the users are mobile, the user demands are placed in different queues having different service capacities and the resulting network is analysed using queueing theory. Furthermore, to achieve optimality in the RA process, an important concept is introduced whereby some demands from one queue are moved to another queue where they have a better chance of enhanced service, thereby giving rise to the possibility of an improvement in the overall performance of the network. The performance results obtained from the analysis, particularly the blocking probability and network throughput, show that the queueing model incorporated into the RA process can help in achieving optimality for the heterogeneous CRN with buffered data.

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