Resource allocation in underlay cognitive radio networks with full-duplex cognitive base station

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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Joint Full-Duplex/Half-Duplex Transmission-Switching Scheduling and Transmission-Energy Allocation in Cognitive Radio Networks with Energy Harvesting

Sensors ◽

10.3390/s18072295 ◽

2018 ◽

Vol 18 (7) ◽

pp. 2295 ◽

Cited By ~ 3

Author(s):

Tran Hoan ◽

Hiep Vu-Van ◽

Insoo Koo

Keyword(s):

Cognitive Radio ◽

Energy Harvesting ◽

Cognitive Radio Networks ◽

Radio Networks ◽

Base Station ◽

Full Duplex ◽

Transmission Protocol ◽

Half Duplex ◽

Cognitive User

The full-duplex transmission protocol has been widely investigated in the literature in order to improve radio spectrum usage efficiency. Unfortunately, due to the effect of imperfect self-interference suppression, the change in transmission power and path loss of non-line-of-sight fading channels will strongly affect performance of full-duplex transmission mode. This entails that the full-duplex transmission protocol is not always a better selection compared to the traditional half-duplex transmission protocol. Considering solar energy-harvesting-powered cognitive radio networks (CRNs), we investigate a joint full-duplex/half-duplex transmission switching scheduling and transmission power allocation in which we utilize the advantages of both half-duplex and full-duplex transmission modes for maximizing the long-term throughput of cognitive radio networks. First, we formulate the transmission rate of half-duplex and full-duplex links for fading channels between cognitive user and base station in which the channel gain is assumed to follow an exponential distribution. Afterward, by considering the availability probability of the primary channel, the limitation of the energy-harvesting capacity of the cognitive user, and the transmission capacity of half-duplex and full-duplex links, we describe the problem in terms of long-term expected throughput. The problem is then solved by adopting the partially observable Markov decision process framework to find the optimal transmission policy for the transmission pair between cognitive user and base station in order to maximize the long-term expected throughput. The optimal policy consists of either the half-duplex or the full-duplex transmission protocols as well as the corresponding amount of transmission energy in each time slot. In addition, to reduce the complexity in formulation and calculation, we also apply the actor–critic-based learning method to solve the considered problem. Finally, the performance of the proposed scheme was evaluated by comparing it with a conventional scheme in which the context of energy harvesting and long-term throughput is not considered.

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Resource Allocation in Spectrum Underlay Cognitive Radio Networks

Dynamic Spectrum Access for Wireless Networks - SpringerBriefs in Electrical and Computer Engineering ◽

10.1007/978-3-319-15299-8_2 ◽

2015 ◽

pp. 13-24

Author(s):

Danda B. Rawat ◽

Min Song ◽

Sachin Shetty

Keyword(s):

Resource Allocation ◽

Cognitive Radio ◽

Cognitive Radio Networks ◽

Radio Networks ◽

Underlay Cognitive Radio ◽

Spectrum Underlay

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