Kerem Kucuk

Scalable location estimation using smart antennas in wireless sensor networks

For Wireless Sensor Networks (WSNs), although many localization techniques have been proposed, development of effective localization techniques for sensor nodes, which do not require any hardware or computational burdens on them, continues to be a challenging task. Motivated by this need, this paper proposes a new location discovery scheme in WSNs so called Sectoral Sweeper based Location Estimation (SSLE). Sectoral Sweeper (SS) relies on integration of smart antenna processing capability only at a central node. By expanding the SS scheme, the key idea in the SSLE is to perform two dimensional (azimuth and range) sweeping process over a given sensor field with beamforming capable central node followed by range estimation and direction estimation algorithms. It does not require any hardware or computational load at tiny sensor nodes. Performance evaluation of the SSLE is given in terms of localization error, response message statistics, and complexity analysis for grid and randomly deployed sensor node scenarios under various sweeping conditions. The SSLE performance is also compared with the Centroid method. The advantage of the SSLE is that it is applicable to environments with hard-to-access sensor deployment scenarios and that desired localization accuracy can be obtained by properly adjusting sweeping parameters.

A novel localization technique for wireless sensor networks using adaptive antenna arrays

In this work, we introduce a novel location estimation technique which uses adaptive antenna arrays (AAA) at the central node in wireless sensor networks (WSN). This localization technique can be used at the setup phase in the routing protocol. This technique is based on scanning the desired region in azimuth and radial directions by changing parameters of downlink beam. This sweeping process can activate the nodes in the desired region which is specified by beamwidth and beamdirection of the transmit beam and also by minimum and maximum thresholds (Rmin and Rmax) for the received signal strength indicator (RSSI). Active nodes in the desired region transmit their IDs and RSSI levels via multi hop communication to the central node. Unlike GPS-based or beacon based localization techniques, the proposed technique does not require any modification in the sensor nodes. The accuracy of location estimation depends on beam direction, beamwidth and transmit power for downlink beams. The results show that by carefully adjusting these parameters, desired performance can be achieved.

A Smart Antenna Module Using OMNeT++ for Wireless Sensor Network Simulation

We introduce a smart antenna (SA) module to be used in OMNeT++ for wireless sensor networks (WSN). This module is a collection of tools in OMNeT++ for adding smart antenna capability to a central node in WSNs. It is based on sectoral sweeper (SS) scheme which was shown to provide efficient task management and easy localization scheme. The number of sensing nodes, energy consumption of nodes, and data traffic carried in the network are reduced with the SS. OMNeT++ is an open source object-oriented modular discrete event network simulator consisting of hierarchically nested modules. With the SA module, desired task region can be specified by a task beam with changing beam width and beam direction parameters in the OMNeT++ configuration file. In addition, each node in the network model that uses SA module has capability of Mobility framework which is intended to support wireless and mobile simulations within OMNeT++. The simulation results provide performance evaluation using the developed module in OMNeT++ for WSNs.

Design and Hardware Implementation of a Novel Smart Antenna Algorithm Using TI DSPs

This paper presents design and implementation of a novel smart antenna algorithm referred as space code correlator (SCC). The algorithm is based on storing predetermined array response vectors, and performing code correlation with the desired users code and then spatial correlation of despread signal with stored array response vectors. The design methodology aims to find a beamforming weight vector that provides satisfactory SINR performance with fixed execution time so that convergence problem is avoided. SCC algorithm is implemented on the different Texas Instruments (TI) TMS320C67x floating-point digital signal processors (DSP) taking into account multipath propagation conditions. The implementation steps and results pertaining weight vector estimation time and SINR performance are presented. Results show that with careful selection of DOA search window and multipath SNR level, the SCC algorithm provides implementation time less than 10 ms frame interval of cdma2000 system

Software radio implementation of a smart antenna system on digital signal processors for cdma2000

This paper presents a software defined radio (SDR) implementation based on programmable digital signal processors (DSP) for smart antenna systems (SAS). We evaluate adaptive beamforming algorithms, namely non-blind-type least mean square (LMS) and blind-type constant modulus (CM) using TI TMS320C6000 high performance DSPs for cdma2000 reverse link. Adaptive beamformers are implemented using TI code composer studio (CCS) that includes assembly language and C code development tools. Performance variation of these sofware radio beamformers in terms of weight computation time and received SINR are compared for different C6000 development boards (TMS320C6701 EVM, TMS320C6711 DSK, and TMS320C6713 DSK) and array topologies under varying multipath propagation conditions. Results show that while antenna array and algorithm type are important for the SINR performance, DSP type becomes important for the weight computation time.

On connectivity analysis of smart antenna capable wireless sensor networks

Advancements in directional antennas or adaptive antenna arrays (AAA) provide potential benefits in solving various problems in wireless sensor network (WSN). Our earlier studies have investigated feasibility of applying smart antennas for task dissemination and localization purposes [4], [6]. Network connectivity or connectivity probability is also an important issue for smart antenna capable WSN as it relies on received “response” packets from the sensor nodes via routing beam. In this study, we analyze the connectivity of smart antenna (SA) capable wireless sensor networks by modeling the WSN network as a random graph and determine connectivity probability (CP) between the sensor nodes. Analytical and simulation results are presented for connectivity probability and number of sensor nodes under different network conditions such as routing beamwidth, node density, and node transmission range. The results provide the practical values for connectivity probability to design smart antenna based WSN localization and shows that the wider beamwidth and/or higher node density in the routing region provides higher CP level.

A modified sectoral sweeper-based localization estimation and its implementation in a multi-hop wireless sensor networking environment by using OPNET

In wireless sensor networks, location awareness along with the sensed data is important for most of the applications. Although there are many localization techniques in the literature, some of these techniques involve tiny sensor nodes, which need to be computationally powerful and complex in hardware to estimate their locations. This paper proposes a modified sectoral sweeper-based localization estimation (M-SSLE) method, which is the improved version of our previously studied SSLE method, to achieve position information of sensor nodes. This technique requires only a central node having a smart antenna capability to estimate locations of sensor nodes and simplified message formats. Using the SSLE technique, the computational burden for location estimation is carried out by a central node and no hardware or software modification to tiny sensor devices is required. The M-SSLE is implemented using an OPNET modeler for realistic fading channel conditions. The detailed implementation methodology in OPNET is presented in terms of node and process models. The performance of the M-SSLE method is evaluated through different network scenarios and channel parameters in terms of localization error, average throughput, and node energy consumption. Furthermore, its localization performance is compared with the SSLE and Cramér Rao Bound methods in the two different scenarios for the deployment of the sensor nodes. The M-SSLE average localization errors of 4.3 and 8.9 m are demonstrated under the log-distance and the log-normal shadowing channel conditions in a 250 m × 250 m area, respectively.

Capacity Improvement for TDD-MIMO Systems via AR Modeling Based Linear Prediction

The quality of channel state information (CSI) affects the performance of multiple input multiple output (MIMO) systems which employ multi-elements antenna arrays at both the transmitter and the receiver. In a time division duplex (TDD) systems, the CSI for downlink can be obtained from uplink channel using reciprocity principal. However, the performance of a MIMO system can be degraded due to channel impairments especially in fast fading scenarios when the CSI obtained from uplink is used for downlink transmission. In this paper, we study performance of autoregressive (AR) modeling based MIMO channel prediction under varying channel propagation conditions (mobile speed, multipath number and angle spread) and prediction filter order. Our simulation results show that using the predicted CSI for downlink provides capacity improvement compared to conventional method.

Evaluation of FPGA-based Software Radio Beamformers for 3G Wireless

This paper presents implementation of some CDMA system compatible antenna array algorithms such as least mean square (LMS), constant modulus (CM) and space code correlator (SCC) on FPGA (such as Xilinx Virtex II Pro FPGA). Implementation issues such as architecture complexity and weight vector computation times are presented. For the signal modeling, cdma2000 reverse link signal model is considered using uniform linear array (ULA) topology. Results show that FPGA based implementation provides relatively short weight vector computation times compared to previously obtained DSP based implementations

RTWiFi‐Lab: A real‐time Wi‐Fi laboratory platform on USRP and LabVIEW for wireless communications education and research

The paper presents the real‐time education and research platform as an effective means for describing wireless and digital communications courses with Wi‐Fi standards. To this end, a Real‐Time Wi‐Fi Laboratory platform, called RTWiFi‐Lab is designed and implemented as part of these courses using NI USRP 2921 and LabVIEW. Laboratory experiments of these courses give benefits for utilizing a hardware platform since these experiments greatly facilitate the understanding of significant effects introduced by real‐time receivers. Hence, this platform is presented with seven experiments that provide the various concepts of these courses for different state‐of‐the‐art wireless and digital communications techniques such as signal detection, data modulation, frequency, phase offset estimation, etc. The RTWiFi‐Lab has been considered to provide computer engineering undergraduate students and qualified graduate students with the basic introduction to wireless and digital communications concepts in a short time at Kocaeli University, Turkey.The paper presents the real-time education and research platform as an effective means for describing wireless and digital communications courses with Wi-Fi standards. To this end, a Real-Time Wi-Fi Laboratory platform, called RTWiFi-Lab is designed and implemented as part of these courses using NI USRP 2921 and LabVIEW. Laboratory experiments of these courses give benefits for utilizing a hardware platform since these experiments greatly facilitate the understanding of significant effects introduced by real-time receivers. Hence, this platform is presented with seven experiments that provide the various concepts of these courses for different state-of-the-art wireless and digital communications techniques such as signal detection, data modulation, frequency, phase offset estimation, etc. The RTWiFi-Lab has been considered to provide computer engineering undergraduate students and qualified graduate students with the basic introduction to wireless and digital communications concepts in a short time at Kocaeli University, Turkey.