Design a WLAN mini access point in the android platform

Mobile as a computing platform is becoming more and more popular. The amount of such devices shipped every year is growing rapidly, more than 1.2 billion in 2009. At the same time the WLAN is being widely adapted at various locations like campuses, meeting rooms, stations, etc. Currently almost all smart phones come with the support for the WLAN. However, most the mobile devices can only behavior as a client in the WLAN. It would be a remarkable feature if the mobile device is able to function as an Access Point (AP) and a modem which forwards data between the 3G network and the WLAN. Android designed for handheld devices has become a popular and powerful platform in both the industry and amateur developer community. Presently there is no WLAN AP mode supported in the Android platform, therefore it’s an interesting task for us to implement such a function. We start with studying the software AP hostapd. We set up a WLAN with hostapd running in a Ubuntu Linux platform, instead of a hardware AP. By doing this we figure out the elements needed to achieve the software AP functionality. Next we explore the Android building system, understand the mechanism the building system works, and learn the way add new modules that we prepare to add into the platform. With these basics we take all the elements needed into Android source code hierarchy and build them into the final executables. Testing cases are given both in Ubuntu Linux platform and the Android platform. To make the user experience better we design an application in the Android platform for controlling the AP built from hostapd and other components. Through the process we have done many experiments and have gained rich experience and knowledge in the Linux operating system, Linux wireless implementation, wireless drivers, Android building system, and Android application development. Some of them are enhancement to the existing knowledge in various websites, and some are new to all the members in the development community. These are all recorded in the thesis. For the final testing we succeed in both steps. First, the peripheral stations can discover the AP in the Android platform and all stations are able to connect to it. There is no difference between connection to the AP in the Android platform and connection to a normal hardware AP device. Secondly, the data packets are successfully transmitted between stations, which means there is no barrier in the AP in the Android platform for providing data service. From the view of networking layering, we conclude that we succeed in both link layer and application layer

Complex amplitudes tracking loop for multi-path channel estimation in OFDM systems: Synthesis and extension

version corrigée (4 corrections en rouge dans les formules par rapport à la publication de la conférence)International audienceThis study deals with pilot-aided multi-path channel estimation for orthogonal frequency division multiplexing (OFDM) systems under slow to moderate fading conditions. Some algorithms exploit the channel time-domain correlation by using Kalman filters (KFs) to track the channel multi-path complex amplitudes (CAs), assuming a primary acquisition of the delays. Recently, it was shown that less complex algorithms, based on a second-order Complex Amplitude Tracking Loop (CATL) structure and a Least-Square (LS) pilot-aided error signal, can also reach near optimal asymptotic mean-squared error (MSE) performance. The LS-CATL-based algorithms are inspired by digital Phase-Locked Loops (PLL), as well as by the "prediction-correction" principle of the KF (in steady-state mode). This paper sums up and extends our previous results for the tuning and steady-state performance of the LS-CATL algorithm: analytic formulae are given for the first-, second-, and third-order loops, usable here for the multi-path multi-carrier scenario, and adaptable to any Doppler spectrum model of wide-sense stationary channels

Simplified Random-Walk-Model-Based Kalman Filter for Slow to Moderate Fading Channel Estimation in OFDM Systems

12 pagesInternational audienceThis study deals with multi-path channel estimation for orthogonal frequency division multiplexing systems under slow to moderate fading conditions. Advanced algorithms exploit the channel time-domain correlation by using Kalman Filters (KFs) based on an approximation of the time-varying channel. Recently, it was shown that under slow to moderate fading, near optimal channel multi-path complex amplitude estimation can be obtained by using the integrated Random Walk (RW) model as the channel approximation. To reduce the complexity of the high-dimensional RW-KF for joint estimation of the multi-path complex amplitudes, we propose using a lower dimensional RW-KF that estimates the complex amplitude of each path separately. We demonstrate that this amounts to a simplification of the joint multi-path Kalman gain formulation through the Woodbury's identities. Hence, this new algorithm consists of a superposition of independent single-path single-carrier KFs, which were optimized in our previous studies. This observation allows us to adapt the optimization to the actual multi-path multi-carrier scenario, to provide analytic formulae for the mean-square error performance and the optimal tuning of the proposed estimator directly as a function of the physical parameters of the channel (Doppler frequency, Signal-to-Noise-Ratio, Power Delay Profile). These analytic formulae are given for the first-, second-, and third-order RW models used in the KF. The proposed per-path KF is shown to be as efficient as the exact KF (i.e., the joint multipath KF), and outperforms the autoregressive-model-based KFs proposed in the literature

On the use of tracking loops for low-complexity multi-path channel estimation in OFDM systems

International audience—This paper treats pilot aided multi-path channel estimation with tracking loops for OFDM systems under slow to moderate fading conditions. Recent works have presented theoretical results for the tuning of second-order and third-order tracking loops in the particular context of Jakes's Doppler spectrum channel. The method for getting the loop coefficients resorted either to the use of a given constraint, which made the obtained coefficients sub-optimal, or was obtained in part by simulations. Here, we perform a global optimization of the coefficients without constraints to get the optimal coefficients, and analytical formulas are provided. One remarkable result of this optimization is that only the natural frequency depends on the transmission parameters, i.e., the channel Doppler spectrum, the power delay profile, and the noise variance. Consequently, only one parameter has to be tuned. Moreover, asymptotic performance is formulated in a more general way as a function of the 2rth moments of the Doppler spectrum (r is the loop order). Hence, all our derivations are usable for any Doppler spectrum and are not specific to Jakes's Doppler spectrum. A complete table sums up for the three orders the theoretical results of the optimal coefficients together with the asymptotic performance. The performance is also compared with that of the asymptotic Kalman filter

Third-Order Kalman Filter: Tuning and Steady-State Performance

4 pagesInternational audienceThis letter deals with the Kalman filter (KF) based on a third-order integrated random walk model (RW3). The resulting filter, noted as RW3-KF, is well suited to track slow time-varying parameters with strong trend behaviour. We first prove that the RW3-KF in steady-state admits an equivalent structure to the third-order digital phase-locked loops (DPLL). The approximate asymptotic mean-squared-error (MSE) is obtained by solving the Riccati equations, which is given in a closed-form expression as a function of the RW3 model parameter: the state noise variance. Then, the closed-form expression of the optimum state noise variance is derived to minimize the asymptotic MSE. Simulation results are given for the particular case where the parameter to be estimated is a Rayleigh channel coefficient with Jakes' Doppler spectrum

Third-order Complex Amplitudes Tracking Loop for Slow Flat Fading Channel On-Line Estimation

12 pagesInternational audienceThis paper deals with channel estimation in tracking mode over a flat Rayleigh fading channel with Jakes' Doppler Spectrum. Many estimation algorithms exploit the time-domain correlation of the channel by employing a Kalman filter based on a first-order (or sometimes second-order) approximation model of the time-varying channel. However, the nature of the approximation model itself degrades the estimation performance for slow to moderate varying channel scenarios. Furthermore, the Kalman-based algorithms exhibit a certain complexity. Hence, a different model and approach has been investigated in this work to tackle all of these issues. A novel PLL-structured third-order tracking loop estimator with a low complexity is proposed. The connection between a steady-state Kalman filter based on a random walk approximation model and the proposed estimator is first established. Then, a sub-optimal mean-squared-error (MSE) is given in a closed-form expression as a function of the tracking loop parameters. The parameters that minimize this sub-optimal MSE are also given in a closed-form expression. The asymptotic MSE and Bit-Error-Ratio (BER) simulation results demonstrate that the proposed estimator outperforms the first and second order Kalman-based filters reported in literature. The robustness of the proposed estimator is also verified by a mismatch simulation

New super-orthogonal space-time trellis codes using differential M-PSK for noncoherent mobile communication systems with two transmit antennas

In this paper, we develop super-orthogonal space-time trellis codes (SOSTTCs) using differential binary phase-shift keying, quadriphase-shift keying and eight-phase shift keying for noncoherent communication systems with two transmit antennas without channel state information at the receiver. Based on a differential encoding scheme proposed by Tarokh and Jafarkhani, we propose a new decoding algorithm with reduced decoding complexity. To evaluate the performance of the SOSTTCs by way of computer simulations, a geometric two-ring channel model is employed throughout. The simulation results show that the new decoding algorithm has the same decoding performance compared with the traditional decoding strategy, while it reduces significantly the overall computing complexity. As expected the system performance depends greatly on the antenna spacing and on the angular spread of the incoming waves. For fair comparison, we also design SOSTTCs for coherent detection of the same complexity as those demonstrated for the noncoherent case. As in the case of classical single antenna transmission systems, the coherent scheme outperforms the differential one by approximately 3 dB for SOSTTCs as well

On the study of faster-than-Nyquist multicarrier signaling based on frame theory

Multicarrier transmissions are classically based on undercomplete or exact Weyl-Heisenberg Riesz (biorthogonal or orthogonal) bases implemented thanks to oversampled filter-banks. This can be seen as a transmission below the Nyquist rate. However, when overcomplete Weyl-Heisenberg frames are used, we obtain a “faster-than-Nyquist” (FTN) system and it is theoretically impossible to recover exactly transmitted symbols using a linear receiver. Various studies have shown the interest of this high density signaling scheme as well as practical implementations based on trellis and/or iterative decoding. Nevertheless, there is still a lack of theoretical justifications with regard to pulse design in the FTN case. In this paper, we consider a linear transceiver operating over an additive white Gaussian noise channel. Using the frame theory and simulation results, we show that the mean squared error (MSE) is minimized when tight frames are used

Estimation of Expected Returns, Time Consistency of A Stock Return Model, and Their Application to Portfolio Selection

Longer horizon returns are modeled by two approaches, which have different impact on skewness and excess kurtosis. The Levy approach, which considers the random variable at longer horizon as the cumulants of i.i.d random variables from shorter horizons, tends to decrease skewness and excess kurtosis in a faster rate along the time horizon than the real data implies. On the other side, the scaling approach keeps skewness and excess kurtosis constant along the time horizon. The combination of these two approaches may have a better performance than each one of them. This empirical work employs the mixed approach to study the returns at five time scales, from one-hour to two-week. At all time scales, the mixed model outperforms the other two in terms of the KS test and numerous statistical distances. Traditionally, the expected return is estimated from the historical data through the classic asset pricing models and their variations. However, because the realized returns are so volatile, it requires decades or even longer time period of data to attain relatively accurate estimates. Furthermore, it is questionable to extrapolate the expected return from the historical data because the return is determined by future uncertainty. Therefore, instead of using the historical data, the expected return should be estimated from data representing future uncertainty, such as the option prices which are used in our method. A numeraire portfolio links the option prices to the expected return by its striking feature, which states that any contingent claim's price, if denominated by this portfolio, is the conditional expectation of its denominated future payoffs under the physical measure. It contains the information of the expected return. Therefore, in this study, the expected returns are estimated from the option calibration through the numeraire portfolio pricing method. The results are compared to the realized returns through a linear regression model, which shows that the difference of the two returns is indifferent to the major risk factors. This demonstrates that the numeraire portfolio pricing method provides a good estimator for the expected return. The modern portfolio theory is well developed. However, various aspects are questioned in the implementation, e.g., the expected return is not properly estimated using historical data, the return distribution is assumed to be Gaussian, which does not reflect the empirical facts. The results from the first two studies can be applied to this problem. The constructed portfolio using this estimated expected return is superior to the reference portfolios with expected return estimated from historical data. Furthermore, this portfolio also outperforms the market index, SPX