• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.6
• /
• pp.1828-1847
• /
• 2014

Coordinated multi-point (CoMP) transmission has been regarded as a potential technology for LTE-Advanced. In frequency division duplexing systems, channel quantization is applied for reporting channel state information (CSI). Considering the dynamic number of cooperation base stations (BSs), asymmetry feature of CoMP channels and high searching complexity, simply increasing the size of the codebook used in traditional multiple antenna systems to quantize the global CSI of CoMP systems directly is infeasible. Per-cell codebook based channel quantization to quantize local CSI for each BS separately is an effective method. In this paper, the theoretical upper bounds of system throughput are derived for two codeword selection schemes, independent codeword selection (ICS) and joint codeword selection (JCS), respectively. The feedback overhead and selection complexity of these two schemes are analyzed. In the simulation, the system throughput of ICS and JCS is compared. Both analysis and simulation results show that JCS has a better tradeoff between system throughput and feedback overhead. The ICS has obvious advantage in complexity, but it needs additional phase information (PI) feedback for obtaining the approximate system throughput with JCS. Under the same number of feedback bits constraint, allocating the number of bits for channel direction information (CDI) and PI quantization can increase the system throughput, but ICS is still inferior to JCS. Based on theoretical analysis and simulation results, some recommendations are given with regard to the application of each scheme respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1761-1777
• /
• 2021

An image with infrared features and visible details is obtained by processing infrared and visible images. In this paper, a fusion method based on Laplacian pyramid and generative adversarial network is proposed to obtain high quality fusion images, termed as Laplacian-GAN. Firstly, the base and detail layers are obtained by decomposing the source images. Secondly, we utilize the Laplacian pyramid-based method to fuse these base layers to obtain more information of the base layer. Thirdly, the detail part is fused by a generative adversarial network. In addition, generative adversarial network avoids the manual design complicated fusion rules. Finally, the fused base layer and fused detail layer are reconstructed to obtain the fused image. Experimental results demonstrate that the proposed method can obtain state-of-the-art fusion performance in both visual quality and objective assessment. In terms of visual observation, the fusion image obtained by Laplacian-GAN algorithm in this paper is clearer in detail. At the same time, in the six metrics of MI, AG, EI, MS_SSIM, Q_abf and SCD, the algorithm presented in this paper has improved by 0.62%, 7.10%, 14.53%, 12.18%, 34.33% and 12.23%, respectively, compared with the best of the other three algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.6
• /
• pp.1379-1397
• /
• 2013

We consider a system where a licensed radio spectrum is shared by multiple primary users(PUs) and secondary users(SUs). As the spectrum of interest is licensed to primary network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to PUs. For this system, we study the joint beamforming and power allocation problem via game theory in this paper. The problem is formulated as a non-cooperative beamforming and power allocation game, subject to the interference constraints of PUs as well as the peak transmission power constraints of SUs. We design a joint beamforming and power allocation algorithm for maximizing the total throughput of SUs, which is implemented by alternating iteration of minimum mean square error based decision feedback beamforming and a best response based iterative power allocation algorithm. Simulation results show that the algorithm has better performance than an existing algorithm and can converge to a locally optimal sum utility.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.2
• /
• pp.234-252
• /
• 2013

Due to the uncertain of connections in Delay Tolerant Networks (DTNs), most routing algorithms in DTNs need nodes to forward the message to others based on the opportunistic contact. The contact is related with the beaconing rate. In particular, nodes have more chances to encounter with each other with bigger beaconing rate, but more energy will be used. On the other hand, if the nodes forward the message to every node all the time, the efficiency of the routing algorithm is better, but it needs more energy, too. This paper tries to exploit the optimal beaconing rate and forwarding rate when the total energy is constraint. First, a theoretical framework is proposed, which can be used to evaluate the performance with different forwarding rate and beaconing rate. Then, this paper formulates a joint optimization problem based on the framework. Through Pontryagin's Maximal Principle, this paper obtains the optimal policy and proves that both the optimal forwarding and beaconing rates conform to threshold form. Simulation results show the accuracy of the theoretical framework. Extensive numerical results show that the optimal policy obtained in this paper is the best.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.1
• /
• pp.414-430
• /
• 2016

Verifier-local revocation (VLR) seems to be the most flexible revocation approaches for any group signature scheme, because it just only requires the verifiers to possess some up-to-date revocation information, but not the signers. Langlois et al. (PKC 2014) proposed the first VLR group signature based on lattice assumptions in the random oracle model. Their scheme has at least Õ(n²) ⋅ log N bit group public key and Õ(n) ⋅ log N bit signature, respectively. Here, n is the security parameter and N is the maximum number of group members. In this paper, we present a simpler lattice-based VLR group signature, which is more efficient by a O(log N) factor in both the group public key and the signature size. The security of our VLR group signature can be reduced to the hardness of learning with errors (LWE) and small integer solution (SIS) in the random oracle model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.3
• /
• pp.1785-1801
• /
• 2017

In recent years, image encryption algorithms have been developed rapidly in order to ensure the security of image transmission. With the assistance of our previous work, this paper proposes a novel chaotic image encryption algorithm based on self-adaptive model and feedback mechanism to enhance the security and improve the efficiency. Different from other existing methods where the permutation is performed by the self-adaptive model, the initial values of iteration are generated in a novel way to make the distribution of initial values more uniform. Unlike the other schemes which is on the strength of the feedback mechanism in the stage of diffusion, the piecewise linear chaotic map is first introduced to produce the intermediate values for the sake of resisting the differential attack. The security and efficiency analysis has been performed. We measure our scheme through comprehensive simulations, considering key sensitivity, key space, encryption speed, and resistance to common attacks, especially differential attack.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.12
• /
• pp.5943-5962
• /
• 2017

A resource allocation algorithm based on simultaneous wireless information and power transfer (SWIPT) to maximize the system throughput is proposed in orthogonal frequency division multiplexing (OFDM) relay networks. The algorithm formulates the problem under the peak power constraints of the source and each subcarrier (SC), and the energy causality constraint of the relay. With the given SC allocation of the source, we give and prove the optimal propositions of the formulated problem. Then, the formulated problem could be decomposed into two separate throughput maximization sub-problems by setting the total power to transfer energy. Finally, several SC allocation schemes are proposed, which are energy priority scheme, information priority scheme, balanced allocation scheme and exhaustive scheme. The simulation results reveal that the energy priority scheme can significantly reduce computational complexity and achieve approximate performance with the exhaustive scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.6
• /
• pp.1166-1191
• /
• 2011

This paper presents an adaptive active tracking system with sector based scanning for a single PTZ camera. Dividing sectors on an image reduces the search space to shorten selection time so that the system can cover many targets. Upon the selection of a target, the system estimates the target trajectory to predict the zooming location with a finite amount of time for camera movement. Advanced estimation techniques using probabilistic reason suffer from the unknown object dynamics and the inaccurate estimation compromises the zooming level to prevent tracking failure. The proposed system uses the simple piecewise estimation with a few frames to cope with fast moving objects and/or slow camera movements. The target is tracked in multiple steps and the zooming time for each step is determined by maximizing the zooming level within the expected variation of object velocity and detection. The number of zooming steps is adaptively determined according to target speed. In addition, the iterative estimation of a zooming location with camera movement time compensates for the target prediction error due to the difference between speeds of a target and a camera. The effectiveness of the proposed method is validated by simulations and real time experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.3
• /
• pp.1315-1329
• /
• 2018

Ciphertext-policy attribute-based encryption (CP-ABE) associates ciphertext with access policies. Only when the user's attributes satisfy the ciphertext's policy, they can be capable to decrypt the ciphertext. Expressivity and security are the two directions for the research of CP-ABE. Most of the existing schemes only consider monotonic access structures are selectively secure, resulting in lower expressivity and lower security. Therefore, fully secure CP-ABE schemes with non-monotonic access structure are desired. In the existing fully secure non-monotonic access structure CP-ABE schemes, the attributes that are set is bounded and a one-use constraint is required by these projects on attributes, and efficiency will be lost. In this paper, to overcome the flaw referred to above, we propose a new fully secure non-monotonic access structure CP-ABE. Our proposition enforces no constraints on the scale of the attributes that are set and permits attributes' unrestricted utilization. Furthermore, the scheme's public parameters are composed of a constant number of group elements. We further compare the performance of our scheme with former non-monotonic access structure ABE schemes. It is shown that our scheme has relatively lower computation cost and stronger security.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.7
• /
• pp.3095-3111
• /
• 2018

Spectrum sensing (SS) is one of the fundamental tasks for cognitive radio. In SS, decisions can be made via comparing the test statistics with a threshold. Conventional adaptive algorithms for SS usually adjust their thresholds according to the radio environment. This paper concentrates on the issue of adaptive SS whose threshold is adjusted based on the Markovian behavior of primary user (PU). Moreover, Bayesian cost is adopted as the performance metric to achieve a trade-off between false alarm and missed detection probabilities. Two novel adaptive algorithms, including Markov Bayesian energy detection (MBED) algorithm and IMBED (improved MBED) algorithm, are proposed. Both algorithms model the behavior of PU as a two-state Markov process, with which their thresholds are adaptively adjusted according to the detection results at previous slots. Compared with the existing Bayesian energy detection (BED) algorithm, MBED algorithm can achieve lower Bayesian cost, especially in high signal-to-noise ratio (SNR) regime. Furthermore, it has the advantage of low computational complexity. IMBED algorithm is proposed to alleviate the side effects of detection errors at previous slots. It can reduce Bayesian cost more significantly and in a wider SNR region. Simulation results are provided to illustrate the effectiveness and efficiencies of both algorithms.