Bingcai Chen

A Novel Problem Model and Solution Scheme for Roadside Unit Deployment Problem in VANETs

AbstractBeing the building block of network infrastructure for Vehicular Ad-hoc Networks (VANETs), Roadside Units (RSUs) can facilitate vehicle-to-vehicle communications and bridge communications between vehicles and the Internet. However, RSUs are expensive and will be in serious shortage state for a relative long time when deploying VANETs gradually. Hence, maximizing expected deployment profit with limited number of RSUs in road network systems is of great importance. In this paper, we create a novel powerful RSU Deployment Problem Model (RDPM) consisting of a road-network model and a profit model. The road-network model in RDPM supports complicated road shapes meanwhile taking into consideration of key influential factors such as lane number, popularity. Since that the optimal RSU deployment solution of a RDPM problem is hard to obtain, we proposed a genetic algorithm based method to solve it heuristically. Simulation results confirm that our proposed method outperforms the exiting typical BEH method.

Internal Collusive Eavesdropping of Interference Alignment Networks

Interference alignment (IA) networks seem secure, due to the fact that signals from the legitimate network may act as interference to disrupt the external eavesdropping. However, when some users inside the network are cooperating to eavesdrop one certain user, it will not be secure any longer. Thus, we concentrate on the eavesdropping attacks in this paper, and propose a novel collusive eavesdropping scheme (CES) in a K- user IA network, where one of the users is eavesdropped by an eavesdropper with the aid of the other (K-2) cooperators. To perform the passive eavesdropping without being noticed by the targeted user, the precoding and decoding matrices of the eavesdropper and cooperators are re-designed, and some of the cooperators should sacrifice their own quality of transmission to help the eavesdropper meet the feasibility condition. Extensive simulation results are provided to show the eavesdropping effectiveness of the proposed CES in IA networks.

Outage Probability Equivalency of Three Typical Relay Selection Schemes for Selective DF Relay Networks with Selection Combining

Outage probability of selective decode-and-forward (DF) relay networks with different relay selection schemes are usually analyzed separately in the literature. In this paper, for selective DF relay networks with selection combining technique, we show that, the three typical relay selection schemes (named as proactive, reactive, and backward reactive relay selection scheme, respectively) are all equivalent with each other in term of outage probability of the networks. Furthermore, this outage probability equivalency is valid even when the wireless channels in the networks are non-identical, interrelated, and with different fading models. Hence, outage probability of a selective DF relay network with one particular relay selection scheme could be obtained indirectly, if necessary, by obtaining the outage probability of the network with another equivalent relay selection scheme but with lower computing complexity.

Outage Analysis of Cognitive AF Relay Networks with Multiple Primary Users and Heterogeneous Non-identical Parameters

In this paper, we investigate outage performance of dual-hop cognitive AF relay networks with multiple primary users (PUs) and heterogeneous non-identical parameters, including non-identical Rayleigh fading channels, non-identical interference power constraints of PUs, and non-identical noise powers in signals. To overcome the analysis complexity resulted from the consideration of heterogeneous non-identical parameters completely, we conduct our analysis in two steps. In the first step, we focus on networks with non-identical Rayleigh fading channels but with identical interference power constraints and identical noise powers. As analysis results, both the exact closed-form expression and asymptotic closed-form expression of the cumulative distribution function of equivalent end-to-end signal-to-noise ratio of the network are obtained. Then in the second step, we propose a method for transforming networks with heterogeneous non-identical parameters into new networks with identical interference power constraints and identical noise powers meanwhile guaranteeing that outage performance of the two networks before and after the transformation are identical. Hence, outage performance of networks with heterogeneous non-identical parameters can be obtained by applying the analysis results in the fist step to the corresponding transformed networks. Numerical simulations validate the correctness of our analysis, and the simulations also indicate that taking multiple PUs and the diversity of the parameters into consideration is of key importance in obtaining a more accurate estimation of outage performance of such networks.

Outage Probability of Cognitive Selective DF Relay Networks with Multiple Primary Nodes and Heterogenous Non-Identical Constraints

Outage probability analysis of cognitive selective DF relay networks with selection combining technique taking into account all the following issues is important: multiple SU relays, multiple PUs, non-identical independent Rayleigh fading channels, non-identical interference power limits of PUs, non-identical maximum transmission power limits of SUs, and non-identical noise powers in signals. However, no existing works solve this task exactly. In this paper, to overcome the complexity in analyzing such non-identical-parameter networks directly, we conduct the analysis in two steps indirectly. In the first step, we obtain outage probability expressions of identical-parameter networks. Then in the second step, we propose a method for transforming a non-identical-parameter network into a new identical-parameter network, meanwhile guaranteeing that the distributions of end-to-end signal to noise ratio of the two networks before and after the transformation are identical. Thus the outage probability of the identical-parameter network can be regarded as outage probability of the corresponding non-identical-parameter network. Numerical simulations validate our analysis results and confirm the feasibility of the two-step indirect analysis approach.

Constructing Longer Sequences Using a New Improved Interleaved Structure

In this letter, a new interleaved structure is improved and its interesting Local Coordinated Shifting (LCS) Property which is helpful in constructing longer sequences is emphasized. Then, making use of the interleaved structure, several methods for constructing perfect ternary sequences and three-level autocorrelation (0, 1) binary sequences are proposed. The LCS property and the demonstrational construction methods imply that this new interleaved structure is an interesting approach for constructing new sequences.