A Study of Propagation in Shenzhen City

Surveying the propagation path loss behavior of Shenzhen city and from the data recorded we can obtain the city’s path loss slopes, which can be comparatively regarded as the reliable bases of system design.

浅水声学通信中的多路径几何信道模型

Using the underwater acoustic channel(UWA)for information dissemination requires a high data rate.However,some phenomena like refraction,reflection,phase shift,and high attenuation are undesirably apparent when the subject of using UWA is raised.Accordingly,sound communication would be a highly challenging task to be accomplished.Therefore,proposing a model of acoustic underwater communication channels is critical because of the multipath interference originating from the surface and bottom of the ocean.In this contribution,a straightforward geometry channel model for vertical and horizontal marine communications is presented.To do so,transmission loss and channel impulse response are analyzed as a function of transmitter and receiver distance,water depth,and reflection rate.The results of the model proposed in this paper are in very good agreement with those available in the literature.Initial findings indicate that the delay spread of horizontal communication with a 1000 m range reaches79 ms and 0.3 s for 30 m vertical communication.

Non-LOS target localization via millimeter-wave automotive radar

This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good results.Firstly,an electromagnetic(EM)wave NLOS multipath propagation model for vehicle scene is established.Subsequently,with the help of available multipath echoes,a complete NLOS vehicle localiza-tion algorithm is proposed.Finally,simulation and experimental results validate the effectiveness of the established EM wave propagation model and the proposed NLOS vehicle localization algorithm.

DOA estimation of coexisted noncoherent and coherent signals via sparse representation of cleaned array covariance matrix

A new direction finding method is presented to deal with coexisted noncoherent and co- herent signals without smoothing operation. First the direction-of-arrival （DOA） estimation task is herein reformulated as a sparse reconstruction problem of the cleaned array covariance matrix, which is processed to eliminate the affection of the noise. Then by using the block of matrices, the information of DOAs which we pursuit are implied in the sparse coefficient matrix. Finally, the sparse reconstruction problem is solved by the improved M-FOCUSS method, which is applied to the situation of block of matrices. This method outperforms its data domain counterpart in terms of noise suppression, and has a better performance in DOA estimation than the customary spatial smoothing technique. Simulation results verify the efficacy of the proposed method.

Synchronized perturbation elimination and DOA estimation via signal selection mechanism and parallel deep capsule networks in multipath environment

State-of-the-art model-driven Direction-Of-Arrival(DOA)estimation methods for multipath signals face great challenges in practical application because of the dependence on the precise multipath model.In this paper,we introduce a framework,based on deep learning,for synchronizing perturbation auto-elimination with effective DOA estimation in multipath environment.Firstly,a signal selection mechanism is introduced to roughly locate specific signals to spatial subregion via frequency domain filters and compressive sensing-based method.Then,we set the mean of the correlation matrix’s row vectors as the input feature to construct the spatial spectrum by the corresponding single network within the parallel deep capsule networks.The proposed method enhances the generalization capability to untrained scenarios and the adaptability to non-ideal conditions,e.g.,lower SNRs,smaller snapshots,unknown reflection coefficients and perturbational steering vectors,which make up for the defects of the previous model-driven methods.Simulations are carried out to demonstrate the superiority of the proposed method.

Dynamic protected lightpath provisioning in mesh WDM networks

This paper investigates the problem of dynamic protected lightpath services provisioning in optical mesh networks employing wavelength division multiplexing (WDM). A variety of schemes for dynamic protected services provisioning have been proposed, supporting a range of tradeoffs among restoration speed, capacity efficiency, and scalability. In this paper, we propose a novel scheme, called p-cycles-based maximum protected working capacity envelope (PC-MPWCE), which can offer an attractive combination of features: ring-like speed, mesh-like capacity efficiency, and good scalability. To evaluate the performance of PC-MPWCE, we compare it via simulation with 1 + 1 automatic protection switching (APS) and two well-known shared backup path protection (SBPP) on NSFNET. Our simulation results show that PC-MPWCE can achieve much better blocking performance than 1 + 1 APS, and perform the similar blocking performance and capacity efficiency as SBPP.