In this letter, we present a method to design an elevation beam pattern mask for spaceborne synthetic aperture radar (SAR) to reduce the range ambiguity. The proposed two-way elevation beam pattern mask, which requires relatively low sidelobe levels only in the direction of strong range ambiguous echoes, can be highly suitable for enhancing the range ambiguity to signal ratio (RASR). The power levels of the different ambiguous echoes are estimated based on the backscattering coefficient model and satellite geometry. To meet the two-way beam pattern mask, both transmit and receive beam patterns are synthesized simultaneously through the minimax algorithm. To confirm the effectiveness of this mask design method, the RASR performance is evaluated by using various swaths.

A radio map is a collection of fingerprints and collected location information. To build more accurate Wi-Fi positioning system (WPS), a more precise radio map should be prepared in advance. Despite GPS signals are usually unreachable in most indoor venues, GPS signals are commonly used as reference locations to tag the collected fingerprints. As a result, WPS has not been able to achieve high performance in accuracy indoors, even if the place is rich in Wi-Fi signals. This paper introduces a novel method to construct a radio map without any use of GPS signals. Users' home or office address is used instead to tag the locations of collected Wi-Fi signals. Since the method utilizes Wi-Fi signals collected indoors, a more precise radio map construction is possible. For evaluation, we tested the method at four deliberately selected residential and downtown areas in Daejeon and Seoul, Korea. Once the data collection rate rises above 50%, the average error distance was within 10m or less. This indicates that address-based crowdsourcing radio map construction can be an effective means to construct global-scale but precise radio maps at low cost.

Research on place extraction has been of interest for the detection of meaningful places that users visit. Because interpretations of meaningful places may be different according to location-based applications, a universal place extraction algorithm that is able to detect all kinds of meaningful places needs to be developed. Unfortunately, most previously proposed place extraction algorithms failed to show high place detection accuracy and also failed to perfectly detect meaningful places. In this work, we propose a new place extraction algorithm that can significantly enhance the accuracy of place extraction. The basic concept of the proposed algorithm is a superstate model, which is an extension of the Hidden Markov Model (HMM); we substituted superstates for the simple probabilistic distributions of the HMM. Our proposed algorithm shows remarkable detection accuracy in place extraction, significantly higher than any other previously proposed algorithms. Furthermore, the proposed algorithm can efficiently operate in mobile environments because its computations are simple.

The multi-input multi-output (MIMO) system with a subcarrier intensity modulation (SIM) scheme in free-space optics (FSO) has a huge merit for ultra wide band communications mainly due to its diversity gain to be able to mitigate the signal scintillation caused by the atmospheric turbulence. In this study, we have analyzed the performance of the orthogonal space-time block codes (OSTBCs) in FSO links. In particular, the power series expressions of the outage probability and average bit error rate (BER) of the OSTBC for any number of antennas are derived in gamma-gamma fading channels using the SIM scheme. According to the analysis, the 3×2 OSTBC scheme could achieve a significantly high signal-to-noise ratio (SNR) gain of 62.5 dB in a strong turbulence regime, and also a moderately high SNR gain of 48 dB in a moderate turbulence regime over the no diversity at the BER of 10-6. Monte Carlo simulation results verify the accuracy of our analysis.

This letter proposes an efficient decoder for signal detection in orthogonal space-time block coded systems employing phase-shift keying modulation without channel state information at the receiver. The proposed decoder consists of a sphere decoder and a QRD-based decoder. Simulation results show that the proposed decoder enables the system to trade off performance improvement against complexity

In this work, we propose a low-complexity maximum-likelihood decoding approach based on QR decomposition (QRD) for signal detection in VBLAST-STBC systems, which employ less receive antennas than transmit antennas. With the example illustration of (6,3) system using rate 3/4 STBC for three transmit antennas, computer simulations are implemented to verify the performance and complexity of the proposed decoder

This letter proposes a very low-complexity maximum-likelihood (ML) detection algorithm based on QR decomposition for the quasi-orthogonal space-time block code (QSTBC) with four transmit antennas, called the LC-ML decoder. The proposed algorithm enables the QSTBC to achieve ML performance with significant reduction in computational load for any high-level modulation scheme.