Handbook on Advancements in SmartAntenna Technologiesfor Wireless Networks

Chen SunATR Wave Engineering Laboratories, Japan

Jun ChengDoshisha University, Japan

Takashi OhiraToyohashi University of Technology, Japan

Hershey • New YorkInformatIon scIence reference

Foreword ..........................................................................................................................................................................xv

Preface ............................................................................................................................................................................xvi

Acknowledgment .............................................................................................................................................................xx

Section IAlgorithms

Chapter IEigencombining: A Unified Approach to Antenna Array Signal Processing ......................................................................1 Constantin Siriteanu, Seoul National University, Korea Steven D. Blostein, Queen’s University, Canada

Chapter IIRobust Adaptive Beamforming .........................................................................................................................................33 Zhu Liang Yu, Nanyang Technological University, Singapore Meng Hwa Er, Nanyang Technological University, Singapore Wee Ser, Nanyang Technological University, Singapore Huawei Chen, Nanyang Technological University, Singapore

Chapter IIIAdaptive Beamforming Assisted Receiver .......................................................................................................................60 Sheng Chen, University of Southampton, UK

Chapter IVOn the Employment of SMI Beamforming for Cochannel Interference Mitigation in Digital Radio ...............................................................................................................................................82 Thomas Hunziker, University of Kassel, Germany

Chapter VRandom Array Theory and Collaborative Beamforming ..................................................................................................94 Hideki Ochiai, Yokohama National University, Japan Patrick Mitran, University of Waterloo, Canada H. Vincent Poor, Princeton University, USA Vahid Tarokh, Harvard University, USA

Chapter VIAdvanced Space-Time Block Codes and Low Complexity Near Optimal Detection for Future Wireless Networks .........................................................................................................................................107 W. H. Chin, Institute for Infocomm Research, Singapore C. Yuen, Institute for Infocomm Research, Singapore

Table of Contents

Chapter VIISpace-Time Modulated Codes for MIMO Channels with Memory ...............................................................................130 Xiang-Gen Xia, University of Delaware, USA Genyuan Wang, Cisco Systems, USA Pingyi Fan, Tsinghua University, China

Chapter VIIIBlind Channel Estimation in Space-Time Block Coded Systems ..................................................................................156 Javier Vía, University of Cantabria, Spain Ignacio Santamaría, University of Cantabria, Spain Jesús Ibáñez, University of Cantabria, Spain

Chapter IXFast Beamforming of Compact Array Antenna ..............................................................................................................183 Chen Sun, ATR Wave Engineering Laboratories, Japan Makoto Taromaru, ATR Wave Engineering Laboratories, Japan Akifumi Hirata, Kyocera Corporation, Japan Takashi Ohira, Toyohashi University of Technology, Japan Nemai Chandra Karmakar, Monash University, Australia

Chapter XDirection of Arrival Estimation with Compact Array Antennas: A Reactance Switching Approach ...................................................................................................................................201 Eddy Taillefer, Doshisha University Miyakodani 1-3, Japan Jun Cheng, Doshisha University Miyakodani 1-3, Japan Takashi Ohira, Toyohashi University of Technology Toyohashi, Japan

Section IIPerformance Issues

Chapter XIPhysics of Multi-Antenna Communication Systems ......................................................................................................217 Santana Burintramart, Syracuse University, USA Nuri Yilmazer, Syracuse University, USA Tapan K. Sarkar, Syracuse University, USA Magdalena Salazar-Palma, Universidad Carlos III de Madrid, Spain

Chapter XIIMIMO Beamforming ......................................................................................................................................................240 Qinghua Li, Intel Corporation, Santa Clara, USA Xintian Eddie Lin, Intel Corporation, Santa Clara, USA Jianzhong (Charlie) Zhang, Samsung, Richardson, USA

Chapter XIIIJoint Beamforming and Space-Time Coding for MIMO Channels ................................................................................264 Biljana Badic, Swansea University, UK Jinho Choi, Swansea University, UK

Chapter XIVAdaptive MIMO Systems with High Spectral Efficiency ...............................................................................................286 Zhendong Zhou, University of Sydney, Australia Branka Vucetic, University of Sydney, Australia

Chapter XVDetection Based on Relaxation in MIMO Systems ........................................................................................................308 Joakim Jaldén, Royal Institute of Technology, Sweden Björn Ottersten, Royal Institute of Technology, Sweden

Chapter XVITransmission in MIMO OFDM Point to Multipoint Networks ......................................................................................328 Wolfgang Utschick, Technische Universität München, Germany Pedro Tejera, Technische Universität München, Germany Christian Guthy, Technische Universität München, Germany Gerhard Bauch, DOCOMO Communications Laboratories Europe GmbH, Germany

Section IIIApplications of Smart Antennas

Chapter XVIISmart Antennas for Code Division Multiple Access Systems ........................................................................................352 Salman Durrani, The Australian National University, Australia Marek E. Bialkowski, The University of Queensland, Australia

Chapter XVIIICross-Layer Performance of Scheduling and Power Control Schemes in Space-Time Block Coded Downlink Packet Systems ...............................................................................................................................................374 Aimin Sang, NEC Laboratories America, USA Guosen Yue, NEC Laboratories America, USA Xiaodong Wang, Columbia University, USA Mohammad Madihian, NEC Corporation of America, USA

Chapter XIXMobile Ad Hoc Networks Exploiting Multi-Beam Antennas .........................................................................................398 Yimin Zhang, Villanova University, USA Xin Li, Villanova University, USA Moeness G. Amin, Villanova University, USA

Chapter XXKey Generation System Using Smart Antenna ...............................................................................................................425 Toru Hashimoto, ATR Wave Engineer Laboratories, Japan Tomoyuki Aono, Mitsubishi Electric Corporation, Japan

Chapter XXISmart Antennas for Automatic Radio Frequency Identification Readers .......................................................................449 Nemai Chandra Karmakar, Monash University, Australia

Section IVExperiments and Implementations

Chapter XXIIField Programmable Gate Array Based Testbed for Investigating Multiple Input Multiple Output Signal Transmission in Indoor Environments ......................................................................................474 Konstanty Bialkowski, University of Queensland, Australia Adam Postula, University of Queensland, Australia Amin Abbosh, University of Queensland, Australia Marek Bialkowski, University of Queensland, Australia

Chapter XXIIIAd Hoc Networks Testbed Using a Practice Smart Antenna with IEEE802.15.4 Wireless Modules ............................................................................................................................................................500 Masahiro Watanabe, Mitsubishi Electric Corporation, Japan Sadao Obana, ATR Adaptive Communications Research Laboratories, Japan Takashi Watanabe, Shizuoka University, Japan

Chapter XXIVWideband Smart Antenna Avoiding Tapped-Delay Lines and Filters ............................................................................513 Monthippa Uthansakul, Suranaree University of Technology, Thailand Marek E. Bialkowski, University of Queensland, Australia

Chapter XXVOmni-, Sector, and Adaptive Modes of Compact Array Antenna ...................................................................................532 Jun Cheng, Doshisha University, Japan Eddy Taillefer, Doshisha University, Japan Takashi Ohira, Toyohashi University of Technology, Japan

About the Contributors ................................................................................................................................................545

Index ...........................................................................................................................................................................558

Detailed Table of Contents

Foreword ..........................................................................................................................................................................xv

Preface ............................................................................................................................................................................xvi

Acknowledgment .............................................................................................................................................................xx

Section IAlgorithms

Chapter IEigencombining: A Unified Approach to Antenna Array Signal Processing ......................................................................1 Constantin Siriteanu, Seoul National University, Korea Steven D. Blostein, Queen’s University, Canada

This chapter unifies the principles and analyses of conventional signal processing algorithms for receive-side smart an-tennas, and compares their performance and numerical complexity. The chapter starts with a brief look at the traditional single-antenna optimum symbol-detector, continues with analyses of conventional smart antenna algorithms, i.e., statistical beamforming (BF) and maximal-ratio combining (MRC), and culminates with an assessment of their recently-proposed superset known as eigencombining or eigenbeamforming. BF or MRC performance fluctuates with changing propagation conditions, although their numerical complexity remains constant. Maximal-ratio eigencombining (MREC) has been de-vised to achieve best (i.e., near-MRC) performance for complexity that matches the actual channel conditions. The authors derive MREC outage probability and average error probability expressions applicable for any correlation. Particular cases apply to BF and MRC. These tools and numerical complexity assessments help demonstrate the advantages of MREC versus BF or MRC in realistic scenarios.

Chapter IIRobust Adaptive Beamforming .........................................................................................................................................33 Zhu Liang Yu, Nanyang Technological University, Singapore Meng Hwa Er, Nanyang Technological University, Singapore Wee Ser, Nanyang Technological University, Singapore Huawei Chen, Nanyang Technological University, Singapore

In this chapter, we first review the background, basic principle and structure of adaptive beamformers. Since there are many robust adaptive beamforming methods proposed in literature, for easy understanding, we organize them into two categories from the mathematical point of view: one is based on quadratic optimization with linear and nonlinear con-straints; the another one is max-min optimization with linear and nonlinear constraints. With the max-min optimization technique, the state-of-the-art robust adaptive beamformers are derived. Theoretical analysis and numerical results are presented to show their superior performance.

Chapter IIIAdaptive Beamforming Assisted Receiver .......................................................................................................................60 Sheng Chen, University of Southampton, UK

Adaptive beamforming is capable of separating user signals transmitted on the same carrier frequency, and thus provides a practical means of supporting multiusers in a space-division multiple-access scenario. Moreover, for the sake of further improving the achievable bandwidth efficiency, high-throughput quadrature amplitude modulation (QAM) schemes have become popular in numerous wireless network standards, notably, in the recent WiMax standard. This contribution fo-cuses on the design of adaptive beamforming assisted detection for the employment in multiple-antenna aided multiuser systems that employ the high-order QAM signalling. Traditionally, the minimum mean square error (MMSE) design is regarded as the state-of-the-art for adaptive beamforming assisted receiver. However, the recent work (Chen et al., 2006) proposed a novel minimum symbol error rate (MSER) design for the beamforming assisted receiver, and it was demon-strated that this MSER design provides significant performance enhancement, in terms of achievable symbol error rate, over the standard MMSE design. This MSER beamforming design is developed fully in this contribution. In particular, an adaptive implementation of the MSER beamforming solution, referred to as the least symbol error rate algorithm, is investigated extensively. The proposed adaptive MSER beamforming scheme is evaluated in simulation, in comparison with the adaptive MMSE beamforming benchmark.

Chapter IVOn the Employment of SMI Beamforming for Cochannel Interference Mitigation in Digital Radio ...............................................................................................................................................82 Thomas Hunziker, University of Kassel, Germany

Many common adaptive beamforming methods are based on a sample matrix inversion (SMI). The schemes can be ap-plied in two ways. The sample covariance matrices are either computed over preambles, or the sample basis for the SMI and the target of the beamforming are identical. A vector space representation provides insight into the classic SMI-based beamforming variants, and enables elegant derivations of the well-known second-order statistical properties of the output signals. Moreover, the vector space representation is helpful in the definition of appropriate interfaces between beamfom-ing and soft-decision signal decoding in receivers aiming at adaptive cochannel interference mitigation. It turns out that the performance of standard receivers incorporating SMI-based beamforming on short signal intervals and decoding of BICM (bit-interleaved coded modulation) signals can be significantly improved by proper interface design.

Chapter VRandom Array Theory and Collaborative Beamforming ..................................................................................................94 Hideki Ochiai, Yokohama National University, Japan Patrick Mitran, University of Waterloo, Canada H. Vincent Poor, Princeton University, USA Vahid Tarokh, Harvard University, USA

In wireless sensor networks, the sensor nodes are often randomly situated, and each node is likely to be equipped with a single antenna. If these sensor nodes are able to synchronize, it is possible to beamform by considering sensor nodes as a random array of antennas. Using probabilistic arguments, it can be shown that random arrays formed by dispersive sensors can form nice beampatterns with a sharp main lobe and low sidelobe levels. This chapter reviews the probabilistic analysis of linear random arrays, which dates back to the early work of Y. T. Lo (1964), and then discusses recent work on the statistical analysis of two-dimensional random arrays originally derived in the framework of wireless sensor networks.

Chapter VIAdvanced Space-Time Block Codes and Low Complexity Near Optimal Detection for Future Wireless Networks .........................................................................................................................................107 W. H. Chin, Institute for Infocomm Research, Singapore C. Yuen, Institute for Infocomm Research, Singapore

Space-time block coding is a way of introducing multiplexing and diversity gain in wireless systems equipped with multiple antennas. There are several classes of codes tailored for different channel conditions. However, in almost all

the cases, maximum likelihood detection is required to fully realize the diversity introduced. In this chapter, we present the fundamentals of space-time block coding, as well as introduce new codes with better performance. Additionally, we introduce the basic detection algorithms which can be used for detecting space-time block codes. Several low complexity pseudo-maximum likelihood algorithms will also be introduced and discussed.

Chapter VIISpace-Time Modulated Codes for MIMO Channels with Memory ...............................................................................130 Xiang-Gen Xia, University of Delaware, USA Genyuan Wang, Cisco Systems, USA Pingyi Fan, Tsinghua University, China

Modulated codes (MC) are error correction codes (ECC) defined on the complex field and therefore can be naturally com-bined with an intersymbol interference (ISI) channel. It has been previously proved that for any finite tap ISI channel there exist MC with coding gain comparing to the uncoded AWGN channel. In this chapter, we first consider space-time MC for memory channels, such as multiple transmit and receive antenna systems with ISI. Similar to MC for single antenna systems, the space-time MC can be also naturally combined with a multiple antenna system with ISI, which provides the convenience of the study. Some lower bounds on the capacities C and the information rates of the MC coded systems are presented. We also introduce an MC coded zero-forcing decision feedback equalizer (ZF-DFE) where the channel is assumed known at both the transmitter and the receiver. The optimal MC design based on the ZF-DFE are presented.

Chapter VIIIBlind Channel Estimation in Space-Time Block Coded Systems ..................................................................................156 Javier Vía, University of Cantabria, Spain Ignacio Santamaría, University of Cantabria, Spain Jesús Ibáñez, University of Cantabria, Spain

This chapter analyzes the problem of blind channel estimation under Space-Time Block Coded transmissions. In particular, a new blind channel estimation technique for a general class of space-time block codes is proposed. The method is solely based on the second-order statistics of the observations, and its computational complexity reduces to the extraction of the main eigenvector of a generalized eigenvalue problem. Additionally, the identifiability conditions associated to the blind channel estimation problem are analyzed, which is exploited to propose a new transmission technique based on the idea of code diversity or combination of different codes. This technique resolves the ambiguities in most of the practical cases, and it can be reduced to a non-redundant precoding consisting in a single set of rotations or permutations of the transmit antennas. Finally, the performance of the proposed techniques is evaluated by means of several simulation examples.

Chapter IXFast Beamforming of Compact Array Antenna ..............................................................................................................183 Chen Sun, ATR Wave Engineering Laboratories, Japan Makoto Taromaru, ATR Wave Engineering Laboratories, Japan Akifumi Hirata, Kyocera Corporation, Japan Takashi Ohira, Toyohashi University of Technology, Japan Nemai Chandra Karmakar, Monash University, Australia

In this chapter, we describe a compact array antenna. Beamforming is achieved by tuning the load reactances at parasitic elements surrounding the active central element. The existing beam forming algorithms for this reactively controlled parasitic array antennas require long training time. In comparison with these algorithms, a faster beamforming algorithm, based on simultaneous perturbation stochastic approximation (SPSA) theory with a maximum cross-correlation coefficient (MCCC) criterion, is proposed in this chapter. The simulation results validate the algorithm. In an environment where the signal-to-interference ratio (SIR) is 0 dB, the algorithm converges within 50 iterations and achieves an output SINR of 10 dB. With the fast beamforming ability and its low power consumption attribute, the antenna makes the mass deployment of smart antenna technologies practical. To give a comparison of the beamforming algorithm with one of the standard beamforming algorithms for a digital beamforming (DBF) antenna array, we compare the proposed algorithm with the least mean square (LMS) beamforming algorithm. Since the parasitic array antenna is in nature an analog antenna, it cannot suppress correlated interference. Here, we assume that the interferences are uncorrelated.

Chapter XDirection of Arrival Estimation with Compact Array Antennas: A Reactance Switching Approach ...................................................................................................................................201 Eddy Taillefer, Doshisha University Miyakodani 1-3, Japan Jun Cheng, Doshisha University Miyakodani 1-3, Japan Takashi Ohira, Toyohashi University of Technology Toyohashi, Japan

This chapter presents direction of arrival (DoA) estimation with a compact array antenna using methods based on reac-tance switching. The compact array is the single-port electronically steerable parasitic array radiator (Espar) antenna. The antenna beam pattern is controlled though parasitic elements loaded with reactances. DoA estimation using an Espar antenna is proposed with the power pattern cross correlation (PPCC), reactance-domain (RD) multiple signal classifica-tion (MUSIC), and, RD estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms. The three methods exploit the reactance diversity provided by an Espar antenna to correlate different antenna output signals measured at different times and for different reactance values. The authors hope that this chapter allows the researchers to appreciate the issues that may be encountered in the implementation of direction-finding application with a single-port compact array like the Espar antenna.

Section IIPerformance Issues

Chapter XIPhysics of Multi-Antenna Communication Systems ......................................................................................................217 Santana Burintramart, Syracuse University, USA Nuri Yilmazer, Syracuse University, USA Tapan K. Sarkar, Syracuse University, USA Magdalena Salazar-Palma, Universidad Carlos III de Madrid, Spain

This chapter presents a concern regarding the nature of wireless communications using multiple antennas. Multi-antenna systems are mainly developed using array processing methodology mostly derived for a scalar rather than a vector problem. However, as wireless communication systems operate in microwave frequency region, the vector nature of electromagnetic waves cannot be neglected in any system design levels. Failure in doing so will lead to an erroneous interpretation of a system performance. The goal of this chapter is to show that when the vector nature of electromagnetic wave is taken into account, an expected system performance may not be realized. Therefore, the electromagnetic effects must be integrated into a system design process in order to achieve the best system design. Many researches are underway regarding this important issue.

Chapter XIIMIMO Beamforming ......................................................................................................................................................240 Qinghua Li, Intel Corporation, Santa Clara, USA Xintian Eddie Lin, Intel Corporation, Santa Clara, USA Jianzhong (Charlie) Zhang, Samsung, Richardson, USA

Transmit beamforming improves the performance of multiple-input multiple-output antenna system (MIMO) by exploit-ing channel state information (CSI) at the transmitter. Numerous MIMO beamforming schemes are proposed in open literature and standard bodies such as 3GPP, IEEE 802.11n and 802.16d/e. This chapter describes the underlying principle, evolving techniques, and corresponding industrial applications of MIMO beamforming. The main limiting factor is the cumbersome overhead to acquire CSI at the transmitter. The solutions are categorized into FDD (Frequency Division Duplex) and TDD (Time Division Duplex) approaches. For all FDD channels and radio calibration absent TDD channels, channel reciprocity is not available and explicit feedback is required. Codebook-based feedback techniques with various quantization complexities and feedback overheads are depicted in this chapter. Furthermore, we discuss transmit/receive (Tx/Rx) radio chain calibration and channel sounding techniques for TDD channels, and show how to achieve channel reciprocity by overcoming the Tx/Rx asymmetry of the RF components.

Chapter XIIIJoint Beamforming and Space-Time Coding for MIMO Channels ................................................................................264 Biljana Badic, Swansea University, UK Jinho Choi, Swansea University, UK

This chapter introduces joint beamforming (or precoding) and space-time coding for multiple input multiple output (MIMO) channels. First, we explain key ideas of beamforming and space- time coding and then we discuss the joint design of beamformer and space-time codes and its benefits. Beamforming techniques play a key role in smart antenna systems as they can provide various features, including spatially selective transmissions to increase the capacity and coverage increase. STC techniques can offer both coding gain and diversity gain over MIMO channels. Thus, joint beamforming and STC is a more practical approach to exploit both spatial correlation and diversity gain of MIMO channels. We believe that joint design will be actively employed in future standards for wireless communications.

Chapter XIVAdaptive MIMO Systems with High Spectral Efficiency ...............................................................................................286 Zhendong Zhou, University of Sydney, Australia Branka Vucetic, University of Sydney, Australia

This chapter introduces the adaptive modulation and coding (AMC) as a practical means of approaching the high spectral efficiency theoretically promised by multiple-input multiple-output (MIMO) systems. It investigates the AMC MIMO systems in a generic framework and gives a quantitative analysis of the multiplexing gain of these systems. The effects of imperfect channel state information (CSI) on the AMC MIMO systems are pointed out. In the context of imperfect CSI, a design of robust near-capacity AMC MIMO system is proposed and its good performance is verified by simula-tion results. The proposed adaptive system is compared with the non-adaptive MIMO system, which shows the adaptive system approaches the channel capacity closer.

Chapter XVDetection Based on Relaxation in MIMO Systems ........................................................................................................308 Joakim Jaldén, Royal Institute of Technology, Sweden Björn Ottersten, Royal Institute of Technology, Sweden

This chapter takes a closer look at a class of MIMO detention methods, collectively referred to as relaxation detectors. These detectors provide computationally advantageous alternatives to the optimal maximum likelihood detector. Previ-ous analysis of relaxation detectors have mainly focused on the implementation aspects, while resorting to Monte Carlo simulations when it comes to investigating their performance in terms of error probability. The objective of this chapter is to illustrate how the performance of any detector in this class can be readily quantified thought its diversity gain when applied to an i.i.d. Rayleigh fading channel, and to show that the diversity gain is often surprisingly simple to derive based on the geometrical properties of the detector.

Chapter XVITransmission in MIMO OFDM Point to Multipoint Networks ......................................................................................328 Wolfgang Utschick, Technische Universität München, Germany Pedro Tejera, Technische Universität München, Germany Christian Guthy, Technische Universität München, Germany Gerhard Bauch, DOCOMO Communications Laboratories Europe GmbH, Germany

This chapter discusses four different optimization problems of practical importance for transmission in point to multi-point networks with a multiple input transmitter and multiple output receivers. Existing solutions to each of the problems are adapted to a multi-carrier transmission scheme by considering the special structure of the resulting space-frequency channels. Furthermore, for each of the problems, suboptimum approaches are presented that almost achieve optimum performance and, at the same time, do not have the iterative character of optimum algorithms, i.e., they deliver a solution in a fixed number of steps. The purpose of this chapter is to give an overview on optimum design of point to multipoint networks from an information theoretic perspective and to introduce non-iterative algorithms that are a good practical alternative to the sometimes costly iterative algorithms that achieve optimality.

Section IIIApplications of Smart Antennas

Chapter XVIISmart Antennas for Code Division Multiple Access Systems ........................................................................................352 Salman Durrani, The Australian National University, Australia Marek E. Bialkowski, The University of Queensland, Australia

This chapter discusses the use of smart antennas in Code Division Multiple Access (CDMA) systems. First, we give a brief overview of smart antenna classification and techniques and describe the issues that are important to consider when applying these techniques in CDMA systems. These include system architecture, array antennas, channel models, trans-mitter and receiver strategies, beamforming algorithms, and hybrid (beamforming and diversity) approach. Next, we discuss modeling of smart antennas systems. We present an analytical model providing rapid and accurate assessment of the performance of CDMA systems employing a smart antenna. Next, we discuss a simulation strategy for an adaptive beamforming system. A comparison between the analytical results and the simulation results is performed followed by a suitable discussion.

Chapter XVIIICross-Layer Performance of Scheduling and Power Control Schemes in Space-Time Block Coded Downlink Packet Systems ...............................................................................................................................................374 Aimin Sang, NEC Laboratories America, USA Guosen Yue, NEC Laboratories America, USA Xiaodong Wang, Columbia University, USA Mohammad Madihian, NEC Corporation of America, USA

In this chapter, we consider a cellular downlink packet data system employing the space-time block coded (STBC) mul-tiple-input-multiple-output (MIMO) scheme. Taking the CDMA high data rate (HDR) system for example, we evaluate the cross-layer performance of typical scheduling algorithms and a point-to-point power control scheme over a time division multiplexing (TDM)-based shared MIMO channel. Our evaluation focuses on the role of those schemes in multi-user diversity gain, and their impacts on medium access control (MAC) and physical layer performance metrics for delay-tolerant data services, such as throughput, fairness, and bit or frame error rate. The cross-layer evaluation shows that the multi-user diversity gain, which comes from opportunistic scheduling schemes exploiting independent channel oscilla-tions among multiple users, can increase the aggregate throughput and reduce the transmission error rate. It also shows that STBC/MIMO and one-bit and multi-bit power control can indeed help the physical and MAC layer performance but only at a risk of limiting the multiuser diversity gain or the potential throughput of schedulers for delay-tolerant bursty data services.

Chapter XIXMobile Ad Hoc Networks Exploiting Multi-Beam Antennas .........................................................................................398 Yimin Zhang, Villanova University, USA Xin Li, Villanova University, USA Moeness G. Amin, Villanova University, USA

This chapter introduces the concept of multi-beam antenna (MBA) in mobile ad hoc networks and the recent advances in the research relevant to this topic. MBAs have been proposed to achieve concurrent communications with multiple neighboring nodes while they inherit the advantages of directional antennas, such as the high directivity and antenna gain. MBAs can be implemented in the forms of multiple fixed-beam directional antennas (MFBAs) and multi-channel smart antennas (MCSAs). The former either uses multiple predefined beams or selects multiple directional antennas and thus is relatively simple; the latter uses smart antenna techniques to dynamically form multiple adaptive beams and thereby provides more robust communication links to the neighboring nodes. The emphases of this chapter lie in the offerings and implementation techniques of MBAs, random-access scheduling for the contention resolution, effect of multipath propagation, and node throughput evaluation.

Chapter XXKey Generation System Using Smart Antenna ...............................................................................................................425 Toru Hashimoto, ATR Wave Engineer Laboratories, Japan Tomoyuki Aono, Mitsubishi Electric Corporation, Japan

The technology of generating and sharing the key as the representative application of smart antennas is introduced. This scheme is based on the reciprocity theorem of radio wave propagation between the two communication parties. The ran-dom and intentional change of antenna directivity that is electrically changed by using such an ESPAR antenna as variable directional antenna is more effective for this scheme, because the propagation environment can be undulated intentionally and the reproducibility of the propagation environment can be decreased.In this chapter, experimental results carried out at many environments are described. From these results, this system has a potential to achieve the “unconditional security.”

Chapter XXISmart Antennas for Automatic Radio Frequency Identification Readers .......................................................................449 Nemai Chandra Karmakar, Monash University, Australia

Various smart antennas developed for automatic radio frequency identification (RFID) readers are presented. The main smart antennas types of RFID readers are switched beam, phased array, adaptive beamforming and multiple input mul-tiple output (MIMO) antennas. New development in the millimeter wave frequency band—60 GHz and aboves exploits micro-electromechanical system (MEMS) devices and nano-components. Realizing the important of RFID applications in the 900 MHz frequency band, a 3x2-element planar phased array antenna has been designed in a compact package at Monash University. The antenna covers 860-960 GHz frequency band with more than 10 dB input return loss, 12 dBi broadside gain and up to 40° elevation beam scanning with a 4-bit reflection type phase shifter array. Once implemented in the mass market, RFID smart antennas will contribute tremendously in the areas of RFID tag reading rates, collision mitigation, location finding of items and capacity improvement of the RFID system.

Section IVExperiments and Implementations

Chapter XXIIField Programmable Gate Array Based Testbed for Investigating Multiple Input Multiple Output Signal Transmission in Indoor Environments ......................................................................................474 Konstanty Bialkowski, University of Queensland, Australia Adam Postula, University of Queensland, Australia Amin Abbosh, University of Queensland, Australia Marek Bialkowski, University of Queensland, Australia

This chapter introduces the concept of Multiple Input Multiple Output (MIMO) wireless communication system and the necessity to use a testbed to evaluate its performance. A comprehensive review of different types of testbeds available in the literature is presented. Next, the design and development of a 2x2 MIMO testbed which uses in-house built antennas, commercially available RF chips for an RF front end and a Field Programmable Gate Array (FPGA) for based signal processing is described. The operation of the developed testbed is verified using a Channel Emulator. The testing is done for the case of a simple Alamouti QPSK based encoding and decoding scheme of baseband signals.

Chapter XXIIIAd Hoc Networks Testbed Using a Practice Smart Antenna with IEEE802.15.4 Wireless Modules ............................................................................................................................................................500 Masahiro Watanabe, Mitsubishi Electric Corporation, Japan Sadao Obana, ATR Adaptive Communications Research Laboratories, Japan Takashi Watanabe, Shizuoka University, Japan

Recent studies on directional media access protocols (MACs) using smart antennas for wireless ad hoc networks have shown that directional MACs outperform against traditional omini-directional MACs. Those studies evaluate the performance mainly on simulations, where antenna beam is assumed to be ideal, i.e., with neither side-lobes nor back-lobes. Propagation conditions are also assumed to be mathematical model without realistic fading. In this paper, we develop at first a testbed for directional MAC protocols which enables to investigate performance of MAC protocols in the real environment. It incorporates ESPAR as a practical smart antenna, IEEE802.15.4/ZigBee, GPS and gyro modules to allow easy installment of different MAC protocols. To our knowledge, it is the first compact testbed with a practical smart antenna for directional MACs. We implement a directional MAC protocol called SWAMP to evaluate it in the real environment. The empirical discussion based on the experimental results shows that the degradation of the protocol with ideal antennas, and that the protocol still achieves the SDMA effect of spatial reuse and the effect of communication range extension.

Chapter XXIVWideband Smart Antenna Avoiding Tapped-Delay Lines and Filters ............................................................................513 Monthippa Uthansakul, Suranaree University of Technology, Thailand Marek E. Bialkowski, University of Queensland, Australia

This chapter introduces the alternative approach for wideband smart antenna in which the use of tapped-delay lines and frequency filters are avoidable, so called wideband spatial beamformer. Here, the principles of operation and performance of this type of beamformer is theoretically and experimentally examined. In addition, its future trends in education and commercial view points are identified at the end of this chapter. The authors hope that the purposed approach will not only benefit the smart antenna designers, but also inspire the researchers pursuing the uncomplicated beamformer operating in wide frequency band.

Chapter XXVOmni-, Sector, and Adaptive Modes of Compact Array Antenna ...................................................................................532 Jun Cheng, Doshisha University, Japan Eddy Taillefer, Doshisha University, Japan Takashi Ohira, Toyohashi University of Technology, Japan

Three working modes, omni-, sector and adaptive modes, for a compact array antenna are introduced. The compact ar-ray antenna is an electronically steerable parasitic array radiator (Espar) antenna, which has only a single-port output, and carries out signal combination in space by electromagnetic mutual coupling among array elements. These features of the antenna significantly reduce its cost, size, complexity, and power consumption, and make it applicable to mobile user terminals. Signal processing algorithms are developed for the antenna. An omnipattern is given by an equal-voltage single-source power maximization algorithm. Six sector patterns are formed by a single-source power maximization algorithm. Adaptive patterns are obtained by a trained adaptive control algorithm and a blind adaptive control algorithm, respectively. The experiments verified the omnipattern, these six sector patterns and the adaptive patterns. It is hope that understanding of the antenna’s working modes will help researcher for a better design and control of array antennas for mobile user terminals.

About the Contributors ...............................................................................................................................................545

Index ..........................................................................................................................................................................558