Current Issue : April - June Volume : 2017 Issue Number : 2 Articles : 7 Articles
Clustering plays an important role in constructing practical network systems. In this paper, we propose a novel\nclustering algorithm with low complexity for dense small cell networks, which is a promising deployment in\nnext-generation wireless networking. Our algorithm is a matrix-based algorithm where metrics for the clustering\nprocess are represented as a matrix on which the clustering problem is represented as the maximization of elements.\nThe proposed algorithm simplifies the exhaustive search for all possible clustering formations to the sequential\nselection of small cells, which significantly reduces the clustering process complexity. We evaluate the complexity and\nthe achievable rate with the proposed algorithm and show that our algorithm achieves almost optimal performance,\ni.e., almost the same performance achieved by exhaustive search, while substantially reducing the clustering process\ncomplexity....
In this paper, we investigate an enhanced relay beamforming design for two-way relay networks (TWRN). In order to\nreduce the computational complexity, we derive a sum of the inverse of the signal-to-noise ratio (SI-SNR) problem\nequivalent to the objective sum-rate (SR) problem. The SI-SNR problem can be reformulated as a simple optimization\nproblem by using the Cholesky decomposition and Cauchy-Schwarz inequality, and solved by the interior-point\nmethod. The numerical results show that the proposed SI-SNR method can not only reduce the computational\ncomplexity but also have the same SR performance as that of the conventional works...
In high-speed railway (HSR) wireless networks, the link quality is greatly time-dependent and location-varying.\nDue to the high randomness, it is challenging to predict the link quality in HSR wireless networks. In this paper,\nwe firstly conducted a certain amount of field measurement campaigns of HSR wireless network link quality. A great\nnumber of practical datasets are collected regarding packet loss rate (PLR) and round-trip time (RTT). Then,\nwe analyzed its changing pattern in different time scales, and further model the link quality of HSR wireless\nnetwork using hidden Markov chain. Based on this, an improved algorithm was developed to simulate the\nvariation of HSR wireless network link quality. Simulation results prove that the proposed model is capable\nof accurately reproducing the behavior of HSR wireless network link quality with regard to PLR and RTT.\nThis work will offer new inspiration to the prediction of link quality for HSR wireless networks....
This paper focuses on the design of maximum ratio transmission (MRT) precoding for multi-user multiple-input\nmultiple-output (MU-MIMO) downlink transmission. Exiting block diagonalization (BD) precoding studies on MUMIMO\nsystems have the high complexity, because the transmitter precoding matrices constructed by singular value\ndecomposition (SVD) are successively calculated twice. The MRT scheme construct precoding vectors aimed at each\nreceived antennas, respectively, so the signals of every antenna are independent. More spatial diversity gain can be\nobtained compared with BD precoding when MRT precoding and maximum ratio combining are employed.\nSimulations show that the proposed algorithm has many gains over the conventional BD precoding in various\nMU-MIMO systems....
Traditional positioning needs lots of measurements between the target and anchors. However, this requirement is\nfaced with significant challenge in the most practical scenarios. The cooperation between mobile nodes is an\neffective solution. In order to avoid large computational complexity, we need to cooperate with neighbors selectively.\nThis paper proposes a novel node selection algorithm based on the Fisher information matrix. We represented\ncooperation information with the equivalent Fisher information matrix and then selected neighbors. Simulation\nresults show that the proposed algorithm is able to improve positioning accuracy obviously compared with\ndistance-based node selection algorithm....
Wireless mobile networks frequently need remote software updates to add or adjust the tasks of mobile nodes.\nSoftware update traffic, particularly in the Internet of Things (IoT), should be carefully handled since attackers can\neasily compromise a number of unattended devices by modifying a piece of code in the software update routine.\nThese attacks are quite realistic and harmful as seen in the real world. To protect lower-powered mobile devices, an\nin-network detection mechanism is preferred. However, due to the mobility of devices, it is difficult to set a network\nmonitor with complete context of software updates. Moreover, even the conventional integrity checks can be fooled\nby a replaced binary code or minimized modification. In this paper, we tackle this problem and propose CodeDog, a\nnew approach to check the integrity of software updates in mobile environments. CodeDog generates a binary code\nwith semantics markers. A validation of those markers proves the control flow semantics was unchanged. It can be\nperformed on program fragments for in-network monitoring to protect incapable devices. Our evaluation result\nshows that CodeDog can prevent attacks in the supply chain with 4.2 % storage overhead....
In this paper, we propose novel non-linear precoders for the downlink of a multi-user MIMO system in the existence\nof multiple eavesdroppers. The proposed non-linear precoders are designed to improve the physical-layer secrecy\nrate. Specifically, we combine the non-linear successive optimization Tomlinson-Harashima precoding (SO-THP) with\nthe generalized matrix inversion (GMI) technique to maximize the physical-layer secrecy rate. For the purpose of\ncomparison, we examine different traditional precoders with the proposed algorithm in terms of secrecy rate as well\nas bit error rate (BER) performance. We also investigate simplified generalized matrix inversion (S-GMI) and\nlattice-reduction (LR) techniques in order to efficiently compute the parameters of the precoders. We further conduct\ncomputational complexity and secrecy-rate analysis of the proposed and existing algorithms. In addition, in the\nscenario without knowledge of the channel state information (CSI) to the eavesdroppers, a strategy of injecting\nartificial noise (AN) prior to the transmission is employed to enhance the physical-layer secrecy rate. Simulation results\nshow that the proposed non-linear precoders outperform existing precoders in terms of BER and secrecy-rate\nperformance....
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