Double-Layer Compressive Sensing Based Efficient DOA Estimation in WSAN with Block Data Loss.

Accurate information acquisition is of vital importance for wireless sensor array network (WSAN) direction of arrival (DOA) estimation. However, due to the lossy nature of low-power wireless links, data loss, especially block data loss induced by adopting a large packet size, has a catastrophic effect on DOA estimation performance in WSAN. In this paper, we propose a double-layer compressive sensing (CS) framework to eliminate the hazards of block data loss, to achieve high accuracy and efficient DOA estimation. In addition to modeling the random packet loss during transmission as a passive CS process, an active CS procedure is introduced at each array sensor to further enhance the robustness of transmission. Furthermore, to avoid the error propagation from signal recovery to DOA estimation in conventional methods, we propose a direct DOA estimation technique under the double-layer CS framework. Leveraging a joint frequency and spatial domain sparse representation of the sensor array data, the fusion center (FC) can directly obtain the DOA estimation results according to the received data packets, skipping the phase of signal recovery. Extensive simulations demonstrate that the double-layer CS framework can eliminate the adverse effects induced by block data loss and yield a superior DOA estimation performance in WSAN.

Efficient Sparse Signal Transmission over a Lossy Link Using Compressive Sensing.

Reliable data transmission over lossy communication link is expensive due to overheads for error protection. For signals that have inherent sparse structures, compressive sensing (CS) is applied to facilitate efficient sparse signal transmissions over lossy communication links without data compression or error protection. The natural packet loss in the lossy link is modeled as a random sampling process of the transmitted data, and the original signal will be reconstructed from the lossy transmission results using the CS-based reconstruction method at the receiving end. The impacts of packet lengths on transmission efficiency under different channel conditions have been discussed, and interleaving is incorporated to mitigate the impact of burst data loss. Extensive simulations and experiments have been conducted and compared to the traditional automatic repeat request (ARQ) interpolation technique, and very favorable results have been observed in terms of both accuracy of the reconstructed signals and the transmission energy consumption. Furthermore, the packet length effect provides useful insights for using compressed sensing for efficient sparse signal transmission via lossy links.

[Association of MMP14 gene polymorphisms and osteoporosis in Zhuang men from Baise region of Guangxi].

OBJECTIVE: To assess the association between membrane type 1 matrix metalloproteinase gene (MT1-MMP, MMP14) polymorphisms and osteoporosis in Zhuang men from Baise region of Guangxi. METHODS: Genotypes of 5 loci (rs1003349, rs3751488, rs2269213, rs2236303 and rs743257) of MMP14 gene in 301 Zhuang men were determined with single base extension methods, and bone mineral density (BMD) at left calcaneus was evaluated with quantitative ultrasound with measured values of broadband ultrasonic attenuation (BUA). The subjects were divided according to BMD into osteoporosis group, osteopenia group and normal bone density group. RESULTS: All selected loci were in Hardy-Weinberg equilibrium (P> 0.05). By multiple linear stepwise regression analysis, polymorphisms of the five loci were not associated with BUA. But a significant higher risk of osteoporosis was found in individuals with MMP14 rs1003349 GT genotype (vs. GG genotype; P<0.05) and rs2236303 CC and CT genotypes (vs. TT genotype; P<0.05). Genetic linkage between rs1003349 and rs2236303 was also discovered (D'= 0.839, r(2) = 0.458, P<0.01). Compared with the normal bone density group, the frequency of a G-T haplotype of rs1003349 and rs2236303 was significantly lower in the osteoporosis group (P<0.05). And the risk of osteoporosis for individuals with G-C and T-C haplotypes was 2.556 (95% CI: 1.029-6.349, P = 0.038) and 5.111 (95% CI: 1.341-19.485, P = 0.011) compared with G-T haplotype. CONCLUSION: Polymorphisms of rs1003349 and rs2236303 loci of MMP14 gene are associated with the susceptibility of osteoporosis in Zhuang men in Guangxi. G-C and T-C haplotypes for loci rs1003349 and rs2236303 may increase the disease risk.