Nuzli Mohamad Anas

Performance analysis of outdoor wireless mesh network using B.A.T.M.A.N. advanced

This paper evaluates a routing protocol called Better Approach to Mobile Ad hoc Networking (B.A.T.M.A.N.) for a wireless mesh network. Specifically, this paper describes the practical deployment of the outdoor wireless mesh network using a PC EngineTM embedded application called the ALIX3 series system. The actual measurement of the outdoor wireless mesh network performance is the utmost importance to evaluate the B.A.T.M.A.N. decentralized routing protocol management. This routing protocol eliminates the need to spread the routing information to each node. Furthermore, B.A.T.M.A.N routing protocol is implemented as a kernel module operating at layer 2 and the routing information is embedded in the data packets. Hence, this paper provides both the experimental and real measurements of the practical outdoor wireless mesh network using B.A.T.M.A.N. routing protocol.

Cognitive Radio test bed experimentation using USRP and Matlab®/Simulink®

Sensing of spectrum holes constitute the fundamental step to utilize spectral resources efficiently in Cognitive Radio (CR). This new technology trends intends to alleviate the scarce and underutilized spectrum issues occurred in traditional fixed spectrum allotment. CR defined as dynamic spectrum usage of unlicensed (secondary) user in opportunistic manner without causing harmful interference to licensed (primary) user. Much recent works presented as either theoretical or simulation approach. However, this paper presents a design prototype of indirect and non-parametric of spectrum sensing method implemented using low-cost Universal Software-defined radio Platform (USRP™). A spectrum-sensing algorithm designed based on energy detection built on top of Matlab®/Simulink® interfaced with a USRP™ main board and SBX transceiver daughterboard; both are Ettus Research product.

Robustness analysis of the improved minimum descriptive length stopping criterion

Most of the turbo decoding stopping criteria assume perfect channel reliability available at the receiver since they require a threshold based on signal-to-noise ratio (SNR) information. However, operational environments can vary according to frame sizes, code structures and channel reliability requirements, further aggravating the difficulty in threshold determination and convergence or non-convergence detection. This paper aims to provide a robustness analysis of improved minimum descriptive length (IMDL) stopping criterion peculiar to these factors: the frame sizes, the channel reliability requirements, the code structures, and the code rate. The robustness analysis is benchmarked to the well-known Genie stopping criterion based on the average iteration number (AIN) and bit error rate (BER) performance.

Design and Implementation of II/4 Shift D-QPSK Baseband Modem Using DSP Techniques

The performance of a digital baseband signal processing system and data transmission rate depends on the modulation technique. One of the famous modulation techniques is II/4 shift Differential-Quadrature Phase Shift Keying (II/4 shift D-QPSK). II/4 D-QPSK is a four level modulation scheme first proposed by Baker in 1962 [1] and is currently the focus of intensive research. The aim of this paper is to design and implement the II/4 D-QPSK baseband modem on the Texas Instruments TMS320C6711 digital signal processor (DSP) with DSP-BIOS technique. The implementation included II/4 D-QPSK signal mapping using a look-up table and raised cosine filtering to reduce Inter-Symbol Interference (ISI), and spectral spreading. This paper also describes the differential detection and data recovery design theory in the demodulator and the theory behind the symbol timing recovery module is introduced.

Enhanced Cross-Entropy Based Stopping Criteria at Low Signal-to-Noise Ratio Regions

This paper presents an enhancement of Cross-Entropy (CE)-based stopping criteria at a low signal-to-noise ratios (SNRs) region. The existing CE-based stopping criteria fail to stop the iteration and cause the maximum iteration at low SNRs. Intuitively, this work enhances the CE stopping criterion by combining with the Average-Entropy (AE) stopping criteria. The work also proposes a set of a stopping rule to distinguish the SNR between low and high region. These approaches are then thoroughly analyses in terms of the required average iteration number (AIN), as well as its bit-error-rate (BER) performance. The simulation results show that the enhanced CE able to reduce the AIN compared to existing CE-based stopping criteria while the BER is maintained. Hence, the enhanced CE-based stopping criterion make the decoder more efficient, in terms of reduction in the time delay while increasing turbo codes performance.

Cognitive Power Adjustment for OFDM-Based Wireless Communication System: An Empirical Study

In this paper, we describe an empirical study on the impact of throughput performance when transmission power is adjusted. This experiment was conducted in an office environment for an OFDM-based wireless communication system such as WiFi 802.11g protocol network. We present a power selection mechanism based on intuitively learning one of the attributes which then triggers the power adjustment. We show that clients similar throughput performance can be obtained at reduced transmission power thus prevent an access point from maximizing power unnecessarily. Our cognitive power adjustment method is potentially useful in extremely dense wireless networks deployment since it is able to prevent from any interference and also to reduce energy consumption of the devices. Our evaluation of this mechanism can reduce the power to 5dB while maintaining the same level of throughput.

Power adjustment in dense deployment network: An empirical study

We describe an empirical study findings on the impact of throughput performance when transmission power is adjusted among access points in close-proximity network devices. The experiment was conducted in an office environment to emulate a dense wireless LAN network. We introduce a power adjustment mechanism based on cognitive learning one of the attributes which then triggers the power selection. We show that clients sufficient throughput performance can be obtained at reduced transmission power thus prevent an access point of maximizing power unnecessarily. We have also evaluated the impact of increasing and reducing power to other neighbouring access points. It was found that the impact was less than 10% difference. However, optimizing the power unnecessarily can lead to inefficiency of energy utilization as well as increase electromagnetic exposure to the human body.

Implementing WiMAX signal detection using reconfigurable processor

An optimized and efficient WiMAX signal detection is proposed using reconfigurable processor, namely the Tensilica Xtensa Processor Core. In this paper, we considered a digital signal processing (DSP) implementation of initial synchronization scheme for time division duplex mode in IEEE 802.16e OFDMA downlink transmission. Taking advantage of distinctive features of WiMAX preamble structure, a custom instructions based on single instruction multiple data (SIMD) technique is deployed to accelerate the extensive calculation process involved. Consequently, numerical data profiling incorporating a number of processor architecture variants is compared in terms of numbers of clock cycles require and code size usage. As a result, this implementation reduces the cycle count by 43% and code size requirement by 46%.

On the performance of SVD estimation in Saleh-Valenzuela channel for UWB system

This paper describes the performance of singular value decomposition (SVD) estimation techniques for multiband orthogonal frequency-division multiplexing (OFDM) of ultra-wideband (UWB) system in Saleh-Valenzuela channel modelling. The performance of SVD estimation is compared against LS and MMSE methods corresponding to zero-padded of a UWB system. The crucial limitation in UWB system is strictly low power transmission leads to many challenges in designing the system. However, most of the conventional channel estimation in frequency domain requires either pre-storing a large matrix or performing real-time matrix inversion, which should be avoided for UWB low complexity implementation. The intuition of this paper is to analyse further the complexity of SVD techniques against least squares (LS) and minimum mean square error (MMSE) estimation method. Consequently, this work implies that the SVD method gives an improvement of 3-5 dB if compared to the LS method while a significant complexity reduction of 57.8% as compared to MMSE methods.