Since the new civil signals, B1C and B2a of Beidou System have been announced and broadcast by the newly launched satellites, how to design GNSS receiver by jointly using multiple signals in order to improve sensitivity, accuracy and so on has been a hot research topic. This paper proposes a joint processing method by jointly utilizing the legacy signal B1I and the new signal B1C both of which are broadcast from the new MGEO/IGSO satellites at the same time. This method can adaptively choose the optimal acquisition algorithm according to the signal-to-noise (SNR) estimation. The parallel search technique that is based on GPU-level parallel optimization strategy is properly designed to improve the executions efficiency. The curves of the detection probability versus the false alarm probability, also called the receiver operating characteristic (ROC), are obtained by Monte Carlo simulations.

In the indoor wireless localization environment, the non-line-of-sight receiving signal and low signal-to-noise ratio are usually strongly dominant issues due to the heavy existence of multipath signals, which also restrict the final wireless localization performance seriously. In this paper, a novel indoor localization algorithm based on 3-D multi-array spatial spectrum fusion (3-D-MSSF), which also uses the channel state information (CSI) under uniform circular array (UCA) structure, is proposed. First, in the data assembly process, the number of antennas and the number of observations can be virtually extended by applying a beam space transformation and smoothing technique by using the observed CSI information. Then, the existing multiple signal classification approach is applied on the smoothed data to jointly estimate the 2-D direction-of-arrival angles and the time-of-flight information from the resulting spatial spectrums at each UCA array. And in the grid-fusion explorer process, the estimated parameters are subsequently transmitted to the aggregation center to calculate the location results of each point relative to each access point, which introduces a grid-refinement algorithm in the search grid to improve the localization precision. While the parameters of interest for the final target position can be estimated from a single fused spatial spectrum, which results from fusing all maximum noise subspaces corresponding to the minimum error between each estimated point in the search grid and every set in the 3-D space-time searching grid. Computer simulation results together with the real application experiments in the indoor environment in terms of source position estimation and corresponding RMSE values are given. The proposed 3-D-MSSF method proves a significant indoor positioning performance, which can achieve the final localization accuracy below 1 m even if the line-of-sight signal is blocked, and there exist only multipath path signals at the receiver.

In this paper, we investigate the issues of initialization and deployment of wireless sensor networks (WSNs) under IEEE 802.11b/g interference and fading channels using frequency hopping (FH). We propose an FH algorithm for WSNs, which is implemented and tested with a pair of nodes employing IPv6 over low power wireless personal area networks (6LoWPAN) standard. The merits and demerits of the proposed FH scheme in WSNs are studied under strong IEEE 802.11b/g interference and frequency selective fading channels. We compare the performance results of the proposed FH scheme with those obtained by single-channel radio in WSNs, and show that FH maintains very reliable data rates in the presence of adverse conditions where the single-channel radio fails. We determine a minimum center frequency offset of channels between IEEE 802.15.4 and IEEE 802.11b/g-based networks, which guarantees the error free network operation of IEEE 802.15.4 using a single channel. We design a second FH procedure comprising only four free channels (15, 20, 25, and 26) of IEEE 802.15.4 standard, and show that in the presence of nearby IEEE 802.11b/g interference, the IEEE 802.15.4 data rate using this method is always 98% and more.

In the period of wireless communication, Indoor positioning systems (IPSs) are getting enormous attention. These systems are construct to attain location information of individuals and objects inside a building. Now a day all the applicable wireless technologies used in this context are Wi-Fi and Bluetooth Low Energy (BLE) based. These advancements are additionally decided for their ease of use, low cost and integration into wireless devices. However, these techniques are having some positioning errors along with specified region. Here, we introduce another wireless technology named Light Fidelity (Li-Fi), the basic convention of this technology is the transfer of information using light illumination by light emitting diodes. This article primarily established a set of evaluation indexes for the performance of these three Wi-Fi, BLE and Li-Fi technologies in indoor positioning scenarios. We compare the predefined IPSs in term of performance and limitations. After then outline the tradeoffs among these systems from the perspective of all evaluation entities. We show experimentally that Li-Fi technology achieves a high efficiency but for accuracy, Wi-Fi is still better than Li-Fi and BLE technology.