Power and sub-channel optimization of JPEG 2000 image transmission over OFDM-based cognitive radio networks

Javadi, Golara; Hajshirmohammadi, Atousa; Liang, Jie

doi:10.1016/j.image.2017.08.002

Cited by 6 publications

(6 citation statements)

References 25 publications

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“…In overlay mode, sophisticated signal processing and coding, such as dirty paper coding (DPC), is used by CR to maintain or improve the communication of PUs while capturing extra spectrum bands for SUs' communications [222]. In this mode, SUs are required to be aware of transmitted data sequences (messages), channel gains as well as the encoding procedure of the sequences (codebooks).…”

Section: B2)mentioning

confidence: 99%

“…In the following, we survey and classify the feasible and already proved resource allocation techniques applicable for multimedia transmission over CRNs in order to guarantee QoS/ QoE as listed in Table IX. B.2.1) Machine Learning-based Resource Allocations Techniques Machine learning is supposed to provide a mechanism to guide the system reconfiguration by knowing the environment perception results and device reconfigurability in order to maximize the utility of the available resources [260]. SUs are aware of their environment in nature, but in order to be Bayesian Model [146], [224], [225] Clustering Algorithm [77], [79] Genetic Algorithm [110], [128], [130], [226] Decision Tree [108] Markov Model [29], [42], [101], [121], [139], [219], [227]- [234] Multi-agent Learning [210], [212], [235], [236] Simulated Annealing [222] Game Theory…”

Section: B2)mentioning

confidence: 99%

“…Specifically, SA is a meta-heuristic to approximate global optimization in a large search space for an optimization problem. The authors in [222] proposed an unequal resource allocation approach based on the priority of the coded bits in image quality for a JPEG 2000 image transmission in CRNs. The bits with more priority were protected using sub-channels with better quality.…”

Section: B2)mentioning

confidence: 99%

“…In [222], the overlay CR was chosen as the access mechanism, which required flexibility in the spectrum shape of the transmitted signals. OFDM offers these types of flexibility by filling the spectral gaps without interfering with PUs.…”

Section: E1) Solutionsmentioning

confidence: 99%

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Multimedia Communication over Cognitive Radio Networks from QoS/QoE Perspective; A Comprehensive Survey

Piran¹

2020

Preprint

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The stringent requirements of wireless multimedia transmission lead to very high radio spectrum solicitation. Although the radio spectrum is considered as a scarce resource, the issue with spectrum availability is not scarcity, but the inefficient utilization. Unique characteristics of cognitive radio (CR) such as flexibility, adaptability, and interoperability, particularly have contributed to it being the optimum technological candidate to alleviate the issue of spectrum scarcity for multimedia communications. However, multimedia communications over CR networks (MCRNs) as a bandwidth-hungry, delay-sensitive, and loss-tolerant service, exposes several severe challenges specially to guarantee quality of service (QoS) and quality of experience (QoE). As a result, to date, different schemes based on source and channel coding, multicast, and distributed streaming, have been examined to improve the QoS/QoE in MCRNs. In this paper, we survey QoS/QoE provisioning schemes in MCRNs. We first discuss the basic concepts of multimedia communication, CRNs, QoS and QoE. Then, we present the advantages of utilizing CR for multimedia services and outline the stringent QoS and QoE requirements in MCRNs. Next, we classify the critical challenges for QoS/QoE provisioning in MCRNs including spectrum sensing, resource allocation management, network fluctuations management, latency management, and energy consumption management. Then, we survey the corresponding feasible solutions for each challenge highlighting performance issues, strengths, and weaknesses. Furthermore, we discuss several important open research problems and provide some avenues for future research.

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Section: B2)mentioning

confidence: 99%

Section: B2)mentioning

confidence: 99%

Section: B2)mentioning

confidence: 99%

Section: E1) Solutionsmentioning

confidence: 99%

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Multimedia Communication over Cognitive Radio Networks from QoS/QoE Perspective; A Comprehensive Survey

Piran¹

2020

Preprint

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“…In Table 2, we mainly compare it with the progressive image restoration algorithm with loss. The progressive restoration technologies are used in [6]- [10], and we also compare our algorithm with the methods using progressive transmission technology [42]- [44] for completeness. As shown in Table 2, in the case of loss restoration, the PSNR that we provide is at least 32.62% higher than those provided by the comparison objects.…”

Section: ) Comparison On Psnrmentioning

confidence: 99%

Progressive Image Restoration Based on CP-ABE With Constant-Size Ciphertext and Constant Bilinear Calculation

2019

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Sharing photos on an open social platform with one-to-many features increases the leakage risk of information of the shared photos. Ciphertext-policy attribute-based encryption (CP-ABE) is a one-to-many public key cryptosystem, and its access policy can be set by data owners. Therefore, if we share the protected image on the social platform and encrypt the restoration parameters of the shared image with CP-ABE, then only the accessor whose attribute set satisfies the access policy of CP-ABE can decrypt the ciphertext corresponding to his/her attribute level and then restore the image with the corresponding sharpness level. Consequently, image information protection is realized in a one-to-many scenario. However, for the existing CP-ABE, only when further shortening its ciphertext, reducing the number of bilinear pairing calculations during decryption, and ensuring flexible access policies is it beneficial for CP-ABE to be widely used in popular smart terminals that can run social software. Furthermore, existing algorithms for restoring images also have room for improvement in terms of time and space requirements. For this reason, we propose a progressive image restoration strategy based on the improved CP-ABE in this paper. For the improvement of CP-ABE, we design a new encryption scheme to achieve a shorter constant-size ciphertext, construct an auxiliary function to help the independent authority centers generate private keys for users in new ways, design a decryption algorithm with only one bilinear pairing calculation, and provide the update algorithms for attribute revocation. Subsequently, we build a distributed CP-ABE based on our improved CP-ABE, and the correctness and security of the proposed CP-ABE algorithm are also proven. In addition, we follow the tree access policy to support the access policy, including AND, OR, NOT and threshold operations simultaneously, to adapt to the requirement of some user attributes that undergo frequent changes. Moreover, based on the atmospheric scattering model, we adopt three algorithms to restore the protected image in the dehazing mode according to the sharpness parameters. Compared with the existing literature, we provide users with not only a flexible and efficient access control strategy, shorter constant-size ciphertext and fewer bilinear calculations but also multiple algorithms for restoring images. The experimental results for six privilege levels demonstrate the superiority of our algorithms in protecting image information. INDEX TERMS CP-ABE, constant-size ciphertext, bilinear pairing calculation, progressive image restoration, atmospheric scattering model.

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Reliable rate-adaptive video transmission over cognitive cellular networks using multiple description scalable coding

2018

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The promise of high-bandwidth and low-latency wireless applications has placed unprecedented stress on the limited spectrum for future 5G networks. Thus, dynamic spectrum sharing has emerged as a promising solution to increase the capacity and the coverage of future cellular networks. In this paper, we tackle the issue of video delivery over cognitive cellular networks using a combination of the legacy licensed bands as well as the spectrum holes left unused in TV bands. To actively react to fluctuating bandwidth, the original video undergoes a multiple description scalable coding (MDSC), whereby the video sequence is fragmented into odd and even sub-streams, then the decomposed video is hierarchically encoded using H.264/SVC to produce two independent descriptions that refine each other. As long as the available licensed radio resources are not sufficient to deliver all the scalable video layers, the cognitive base station exploits the available portion of TV spectrum using a hybrid interweave and underlay approach to extend the capacity of the legacy infrastructure. Numerical simulations show that the proposed transmission scheme provides enough capacity, up to 1.62 Mbps increase, to handle the rising demands in terms of video quality in a timely manner without disrupting the primary link and without connection release. Moreover, the proposed MDSC framework offers an increment of 20% (24%, respectively) in the PSNR (MS-SSIM, respectively) of the received video. KeywordsDynamic spectrum sharing • Mobile networks • TV white space • Scalable coding • Multiple description coding Recent studies show that spectrum shortage is a result of the outdated spectrum management policy rather than phys-B Abdelaali Chaoub

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Power and sub-channel optimization of JPEG 2000 image transmission over OFDM-based cognitive radio networks

Cited by 6 publications

References 25 publications

Multimedia Communication over Cognitive Radio Networks from QoS/QoE Perspective; A Comprehensive Survey

Multimedia Communication over Cognitive Radio Networks from QoS/QoE Perspective; A Comprehensive Survey

Progressive Image Restoration Based on CP-ABE With Constant-Size Ciphertext and Constant Bilinear Calculation

Reliable rate-adaptive video transmission over cognitive cellular networks using multiple description scalable coding

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