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    Investigation of Uplink and Downlink Performance ofInvestigation of Uplink and Downlink Performance ofInvestigation of Uplink and Downlink Performance ofInvestigation of Uplink and Downlink Performance of

    DirectivityDirectivityDirectivityDirectivity

    Controlled Constrained Beamforming Algorithms forControlled Constrained Beamforming Algorithms forControlled Constrained Beamforming Algorithms forControlled Constrained Beamforming Algorithms for

    CDMA-Based SystemsCDMA-Based SystemsCDMA-Based SystemsCDMA-Based Systems

    Holger Boche and Martin SchubertHolger Boche and Martin SchubertHolger Boche and Martin SchubertHolger Boche and Martin Schubert

    Heinrich-Hertz-Institut fr Nachrichtentechnik Berlin GmbHHeinrich-Hertz-Institut fr Nachrichtentechnik Berlin GmbHHeinrich-Hertz-Institut fr Nachrichtentechnik Berlin GmbHHeinrich-Hertz-Institut fr Nachrichtentechnik Berlin GmbH

    Broadband Mobile Communication NetworksBroadband Mobile Communication NetworksBroadband Mobile Communication NetworksBroadband Mobile Communication Networks

    Einsteinufer 37, D-10587 Berlin/GermanyEinsteinufer 37, D-10587 Berlin/GermanyEinsteinufer 37, D-10587 Berlin/GermanyEinsteinufer 37, D-10587 Berlin/Germany

    E-mail: [email protected]hi.de, [email protected] / Tel: +49 (0)30-31002-399E-mail: [email protected], [email protected] / Tel: +49 (0)30-31002-399E-mail: [email protected], [email protected] / Tel: +49 (0)30-31002-399E-mail: [email protected], [email protected] / Tel: +49 (0)30-31002-399

    AbstractAbstractAbstractAbstract

    This paper investigates the applicability of the blind DoA-based maximumThis paper investigates the applicability of the blind DoA-based maximumThis paper investigates the applicability of the blind DoA-based maximumThis paper investigates the applicability of the blind DoA-based maximum

    directivity (MD) beamformer to CDMA-based systems in up- and downlink. Ourdirectivity (MD) beamformer to CDMA-based systems in up- and downlink. Ourdirectivity (MD) beamformer to CDMA-based systems in up- and downlink. Ourdirectivity (MD) beamformer to CDMA-based systems in up- and downlink. Our

    approach is based on DoA estimation and consequently does not require any pilotapproach is based on DoA estimation and consequently does not require any pilotapproach is based on DoA estimation and consequently does not require any pilotapproach is based on DoA estimation and consequently does not require any pilot

    signal or training sequence. It is shown how knowledge of the DoA can be usedsignal or training sequence. It is shown how knowledge of the DoA can be usedsignal or training sequence. It is shown how knowledge of the DoA can be usedsignal or training sequence. It is shown how knowledge of the DoA can be used

    to generate a most robust beam pattern in order to perform spatial filtering ofto generate a most robust beam pattern in order to perform spatial filtering ofto generate a most robust beam pattern in order to perform spatial filtering ofto generate a most robust beam pattern in order to perform spatial filtering of

    multipath components in up- and downlink. Robustness is achieved bymultipath components in up- and downlink. Robustness is achieved bymultipath components in up- and downlink. Robustness is achieved bymultipath components in up- and downlink. Robustness is achieved by

    maximising the directivity of the beam pattern as well as by generating broadmaximising the directivity of the beam pattern as well as by generating broadmaximising the directivity of the beam pattern as well as by generating broadmaximising the directivity of the beam pattern as well as by generating broad

    nulls. Analytical results are presented and different aspects of directivitynulls. Analytical results are presented and different aspects of directivitynulls. Analytical results are presented and different aspects of directivitynulls. Analytical results are presented and different aspects of directivity

    controlled beamforming are discussed.controlled beamforming are discussed.controlled beamforming are discussed.controlled beamforming are discussed.

    I INTRODUCTIONI INTRODUCTIONI INTRODUCTIONI INTRODUCTION

    Wireless cellular communication based on DS-CDMA has experienced tremendous

    growth in markets, technology and range of services throughout the last decade.

    However, radio spectrum is a limited resource. The resulting challenge is to develop

    enhanced transmission techniques in order to realise emerging broadband services and

    applications. One promising way to significantly increase the spectral efficiency is the

    deployment of antenna arrays at the base station in order to perform space-time

    processing (STP)[1, 2, 3]

    . While the deployment of antenna arrays in 3rdgeneration

    systems is still optional, they will be an essential part of future systems[4].

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    Exploitation of the spatial dimension can be used to reduce co-channel interference

    (CCI) and inter-symbol interference (ISI), while improving resistance to fading and

    thermal noise. Reducing intra- and inter-cell CCI can be traded for improved coverage,

    capacity or quality. Thus, spatial filtering, also referred to as beamforming[5], will play

    an important role in future broadband wireless networks.

    In this paper, we focus on so-called blind DoA-based beamforming techniques, assuming

    that the direction-of-arrival (DoA) of the dominant transmission paths are known. Blind

    techniques do not need any training sequence or pilot signal. Thus, they consume no

    additional spectrum resource (note that in GSM 20% of the bits are dedicated for

    training). This makes them promising candidates for various types of wireless networks.

    DoA estimates can be obtained with second order statistics of the communication

    signals[6], which are assumed to be stationary within the coherence time of the channel.

    Improvement can be achieved by mobility models, which help predicting the movement

    of the mobile unit by considering the slowly time varying nature of the user location.

    However, the wireless radio channel poses a great challenge as a medium for reliable

    high speed communications and accurate DoA-estimation is difficult to realize. First field

    trials [7, 8] have shown that DoA-based methods are very sensitive to error effects.

    Consequently, DoA-based beamforming must take into account a DoA mismatch of

    several degrees. Conventional DoA-based beamforming has been shown to perform poor

    in this case. This is mostly due to beam pattern distortion caused by hyper-sensitive

    algorithms in presence of DoA errors. Thus, the deployment of DoA-based beamforming

    in mobile environments demands for more robust techniques being able to cope with

    numerous error effects like inter-cell CCI, scattering effects or DoA estimation errors.

    Consequently, the investigation of the beam pattern is an important aspect and new

    performance parameters are needed to assess the quality of the beam pattern.

    In this paper we will focus on the impact of directivity and broad nulls on STP

    architectures for CDMA-based systems. It will be shown how these parameters can be

    used to generate a beam pattern having maximum directivity. Robust beam pattern

    control is envisaged which must compensate for DoA errors, angle spread and CCI.

    We assume a single cell scenario without inter-cell CCI, where all users are separated

    by quasi-orthogonal spreading codes. The cell is divided in three sectors of 120. For

    each sector a uniform linear antenna array(ULA) is deployed at the base station. Linear

    arrays have been developed vigorously during the last decades mainly for radar and

    sonar signal environments in military applications. Its application to mobile

    communications is subject of ongoing world wide research and development activity [1, 2].

    The paper is organised as follows. In Section II we will briefly introduce the underlying

    vector channel model and discuss the angle spread of dominant transmission paths.

    Next, in Section III we discuss different aspects of directivity controlled beamforming

    and broad nulls with respect to space-time processing. The maximum directivity (MD)

    beamformer is presented and its application up- and downlink processing is discussed.

    Finally, we conclude with a summary in Section IV.

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    Some notational conventions are: scalars in lower case, matrices in upper case and

    vectors in boldface lowercase. The expectation operator is written as E[ ]. The complex

    conjugate and the complex conjugate transpose are given by ( ) and ( )H, respectively.

    II SIGNAL AND CHANNEL MODELII SIGNAL AND CHANNEL MODELII SIGNAL AND CHANNEL MODELII SIGNAL AND CHANNEL MODEL

    Consider a narrowband signal s(t) = u(t)ejw 0t, where u(t) denotes the complex

    baseband envelope and w0 the carrier frequency. The signal source is assumed to

    lie in in the far field of a ULA consisting of M isotropic antenna elements with half

    wavelength element spacing. In this case, a plane wave front crosses the array with

    the angle of incidence array elements with the azimuth angle , as depicted in Fig.

    1. For convenience it is assumed that all users and the array lie in a horizontal

    plane, but all results can be extended by the elevation angle.

    Fig. 1: Plane wave front crossing a ULAFig. 1: Plane wave front crossing a ULAFig. 1: Plane wave front crossing a ULAFig. 1: Plane wave front crossing a ULA

    If the ratio of the array aperture to the velocity of light is much smaller than the

    inverse of the bandwidth of the signal, then u(t) can be regarded as constant during the

    propagat