Fast Adaptive S-ALOHA Scheme for Event-driven Machine-to-Machine Communications

Machine-to-Machine (M2M) communication is now playing a market-changing role in a wide range of business world. However, in event-driven M2M communications, a large number of devices activate within a short period of time, which in turn causes high radio congestions and severe access delay. To address this issue, we propose a Fast Adaptive S-ALOHA (FASA) scheme for M2M communication systems with bursty traffic. The statistics of consecutive idle and collision slots, rather than the observation in a single slot, are used in FASA to accelerate the tracking process of network status. Furthermore, the fast convergence property of FASA is guaranteed by using drift analysis. Simulation results demonstrate that the proposed FASA scheme achieves near-optimal performance in reducing access delay, which outperforms that of traditional additive schemes such as PB-ALOHA. Moreover, compared to multiplicative schemes, FASA shows its robustness even under heavy traffic load in addition to better delay performance.Comment: 5 pages, 3 figures, accepted to IEEE VTC2012-Fal

Wind speed retrieval from the Gaofen-3 synthetic aperture radar for VV- and HH-polarization using a re-tuned algorithm

In this study, a re-tuned algorithm based on the geophysical model function (GMF) C-SARMOD2 is proposed to retrieve wind speed from Synthetic Aperture Radar (SAR) imagery collected by the Chinese C-band Gaofen-3 (GF-3) SAR. More than 10,000 Vertical-Vertical (VV) and Horizontal-Horizontal (HH) polarization GF-3 images acquired in quad-polarization stripmap (QPS) and wave (WV) modes have been collected during the last three years, in which wind patterns are observed over open seas with incidence angles ranging from 18° to 52°. These images, collocated with wind vectors from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis at 0.125° resolution, are used to re-tune the C-SARMOD2 algorithm to specialize it for the GF-3 SAR (CSARMOD-GF). In particular, the CSARMOD-GF performs differently from the C-SARMOD2 at low-to-moderate incidence angles smaller than about 34°. Comparisons with wind speed data from the Advanced Scatterometer (ASCAT), Chinese Haiyang-2B (HY-2B) and buoys from the National Data Buoy Center (NDBC) show that the root-mean-square error (RMSE) of the retrieved wind speed is approximately 1.8 m/s. Additionally, the CSARMOD-GF algorithm outperforms three state-of-the-art methods – C-SARMOD, C-SARMOD2, and CMOD7 – that, when applied to GF-3 SAR imagery, generating a RMSE of approximately 2.0–2.4 m/s

Fast frequency-hopping dynamic multiple-access for cognitive radios: Suboptimum noncoherent maximum-likelihood multiuser detection

We propose a novel dynamic multiple-access (DMA) scheme for application in cognitive radios (CRs). This DMA scheme is implemented by fast frequency hopping with $M$-ary frequency-shift keying (FFH/MFSK) associated with suboptimum noncoherent maximum-likelihood multiuser detection (ML-MUD). In our studies, we assume that the primary users (PUs) and the cognitive radio users (CRUs) are operated in the interweave paradigm. The PUs activate to communicate according to a Poisson process and the duration of an activation obeys exponential distribution. The bit error rate (BER) and throughput performance of the dynamic FFH/MFSK systems are investigated by simulations, when assuming communications over Rayleigh fading channels. Our studies and simulation results demonstrate that the dynamic FFH/MFSK with suboptimum noncoherent ML-MUD constitutes one of the promising candidates for DMA in CRs. It has low-complexity and employs high-flexibility for DMA and seamless transition between different frequency bands