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  • 1.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hammarwall, David
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Beamforming utilizing channel norm feedback in multiuser MIMO systems2007In: IEEE Workshop on Signal Processing Advances in Wireless Communications, IEEE , 2007, Vol. SPAWC, p. 1-5Conference paper (Refereed)
    Abstract [en]

    The problem of beamforming and rate estimation in a multi-user downlink multiple-input multiple-output (MIMO) system with limited feedback and statistical channel information at the transmitter is considered. In order to exploit the spatial properties of the channel, the norm of the channel to each receive antenna is computed. We propose to feed back the largest norm to the transmitter and derive the conditional second and fourth order channel moments in order to design the downlink beamforming weights. Similar approaches have previously been presented for multi-user multiple-input single-output (MISO) systems. Herein, these techniques are generalized to MIMO systems, by either antenna selection or receive beamforming at the receiver. Two eigenbeamforming strategies are proposed and shown to outperform opportunistic beamforming, based on similar feedback information.

  • 2.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hammarwall, David
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Zakhour, Randa
    Institut Eurécom, 2229 route des crêtes, BP 193, F-06560, Sophia Antipolis, France.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Gesbert, David
    Institut Eurécom, 2229 route des crêtes, BP 193, F-06560, Sophia Antipolis, France.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Feedback design in multiuser MIMO systems using quantization splitting and hybrid instantaneous/statistical channel information2008In: ICT-MobileSummit 2008 Conference Proceedings / [ed] Paul Cunningham and Miriam Cunningham, IIMC International Information Management Corporation , 2008, , p. 8Conference paper (Refereed)
    Abstract [en]

    In the design of next generation multiuser communication systems, multiple antenna transmission is an essential part providing spatial multiplexing gain and allowing efficient use of resources. A major limiting factor in the resource allocation is the amount of channel state information (CSI) available at the transmitter, particularly in multiuser systems where the feedback from each user terminal must be limited. To this effect we propose two independent approaches for an efficient representation of the channel in multiuser MIMO systems. In the first approach, channel quantization is considered where the total number of feedback bits is limited. A resource allocation scheme is proposed where the available rate is split between the scheduling phase, where all users feed back a coarse CSI quantization, and the precoding phase where the selected receivers refine their CSI. The optimum splitting of the available feedback rate provides a large increase in performance and even simple heuristic splitting gives a noticeable advantage. In the second approach, we exploit a combination of instantaneous and statistical channel information. For spatially correlated Rayleigh and Ricean channels, it is shown that the CSI to large extent can be represented by the channel norm when the long-term channel statistics are known. Within a minimum mean square error (MMSE) estimation framework, feedback of a few bits of the quantized channel norm is sufficient to perform efficient resource allocation and achieve performance close to that of full CSI.

  • 3.
    Hammarwall, David
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Resource Allocation in Multi-Antenna Communication Systems with Limited Feedback2007Doctoral thesis, monograph (Other scientific)
    Abstract [en]

    The use of multiple transmit antennas is considered a key ingredient to significantly improve the spectral efficiency of wireless communication systems beyond that of currently employed systems. Transmit beamforming schemes have been proposed to exploit the spatial characteristics of multi-antenna radio channels; that is, multiple-input single-output (MISO) channels. In multiuser communication systems, the downlink throughput can be significantly increased by simultaneously transmitting to several users in the same timefrequency slot, by means of spatial-division multi-access (SDMA). Several SDMA beamforming algorithms are available for joint optimal beamforming and power control for the downlink. Such optimal beamforming minimizes the total transmission power, while ensuring an individual target quality of service (QoS) for each user; alternatively the weakest QoS is maximized, subject to a transmit power constraint.

    In this thesis, both of these formulations are considered and some of the available algorithms are generalized to enable quadratic shaping constraints on the beamformers. By imposing additional constraints, the QoS measure can be extended to take factors other than the customary signal to interference-plus-noise ratio (SINR) into account. Alternatively, other limitations such as interference requirements or physical constraints may be incorporated in the optimization. The proposed beamforming algorithms are also based on a more general SINR expression than previously analyzed in this context. The generalized SINR expression allows for more accurate modeling; for example, non-zero self interference can be modeled in code-division multi-access (CDMA) systems.

    A major limiting factor for downlink resource allocation is the amount of channel-state information (CSI) available at the base station. In most cases, CSI can be estimated only at the receivers, and then fed back to the base station. This procedure typically constrains the amount of CSI that can be conveyed. In this thesis, a minimum mean squared-error (MMSE) SINR estimation framework is proposed, which combines partial CSI with channel-distribution information (CDI); the CDI varies slowly and is assumed to be known at the transmitter. User selection (scheduling) and beamforming techniques, suitable for the MMSE SINR estimates, are also proposed.

    Special attention is given to the feedback of a scalar channel-gain information (CGI) parameter. The CSI provided by CGI feedback is studied in depth for correlated Rayleigh and Ricean fading channels. It is shown, using asymptotic analysis, that large realizations of the CGI parameter convey additional spatial CSI at the transmitter; the proposed scheme is thus ideal for multiuser diversity transmission schemes, where resources are allocated only to users experiencing favorable channel conditions. It is shown by numerical simulations that, in wide-area scenarios, feeding back a single scalar CGI parameter per user, provides sufficient information for the proposed downlink resource-allocation algorithms to perform efficient SDMA beamforming and user selection

  • 4.
    Hammarwall, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Acquiring partial CSI for spatially selective transmission by instantaneous channel norm feedback2008In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 56, no 3, p. 1188-1204Article in journal (Refereed)
    Abstract [en]

    In the design of next-generation multiuser communication systems, multiple-antenna transmission is an essential part providing additional spatial degrees of freedom and allowing efficient use of resources. A major limiting factor in the resource allocation is the amount of channel state information (CSI) available at the transmitter, particularly in multiuser systems where the feedback from each user terminal must be limited. Herein, we show that the Euclidean norm of the instantaneous channel, when combined with long-term channel statistics provides sufficient information for the transmitter to efficiently utilize multiuser diversity in time, frequency, and space. We consider the downlink of a communication system where the base station has multiple transmit antennas whereas each user terminal has a single receive antenna. The CSI provided by channel statistics and feedback of the norm of the instantaneous channel vector is studied in depth for correlated Rayleigh and Ricean fading channels, within a minimum mean-square error (MMSE) estimation framework. An asymptotic analysis (high instantaneous SNR) is presented which shows that channel realizations with large channel norm provide additional spatial CSI at the transmitter. This makes the proposed scheme ideal for multiuser diversity transmission schemes, where resources are only allocated to users experiencing favorable channel conditions.

  • 5.
    Hammarwall, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Beamforming and user selection in SDMA systems utilizing channel statistics and instantaneous SNR feedback2007In: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE , 2007, p. 113-116Conference paper (Refereed)
    Abstract [en]

    Spatial division multiple access (SDMA) systems efficiently take advantage of the spatial dimensions of the channel to increase the performance of the system. A major difficulty, common to all SDMA systems, is the requirement of channel knowledge at the transmitter to enable transmission of multiple streams without catastrophic interference. Herein we show that, in wide area scenarios, statistical channel information combined with the Euclidean norm of the channel realization, fed back from the users, provide sufficient information for SDMA systems to efficiently allocate users in time and space. A joint beamforming and scheduling algorithm is proposed for the downlink, which extends the proportional fair scheduling criterion to an SDMA setting, resulting in a weighted sum rate maximization.

  • 6.
    Hammarwall, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    On downlink beamforming with indefinite shaping constraints2006In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 54, no 9, p. 3566-3580Article in journal (Refereed)
    Abstract [en]

    Beamforming schemes have been proposed to exploit the spatial characteristics of multiple-input single-output (MISO) wireless radio channels. Several algorithms are available for optimal joint beamforming and power control for the downlink. Such optimal beamforming minimizes the total transmission power, while ensuring an individual target quality of service (QoS) for each user; alternatively the weakest QoS is maximized, subject to a power constraint. Herein, we consider both formulations and some of the available algorithms are generalized to enable indefinite quadratic shaping constraints on the beamformers. By imposing such additional constraints, the QoS measure can be extended to take other factors than the customary signal-to-interference-and-noise ratio (SINR) into account. Alternatively, other limitations such as interference requirements or physical constraints may be handled within the optimization. We also consider a more general SINR expression than previously analyzed, which allows for more accurate modeling, e.g., of nonzero self-interference in code-division multiple-access (CDMA) systems. Several applications for indefinite equality or inequality constraints are suggested and evaluated. For example, it is shown how such constraints may be used to ensure a minimum level of path diversity in a CDMA system. Other applications include limiting intercell interference in decentralized systems

  • 7.
    Hammarwall, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Utilizing the spatial information provided by channel norm feedback in SDMA systems2008In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 56, no 7, p. 3278-3293Article in journal (Refereed)
    Abstract [en]

    To achieve high performance, in terms of reliability and throughput, in future multiple-antenna communication systems, it is essential to fully exploit the spatial dimensions of the wireless propagation channel. In multiuser communication systems, the throughput can be significantly increased by simultaneously transmitting to several users in the same time-frequency slot by means of spatial-division multi-access (SDMA). A major limiting factor for downlink SDMA transmission is the amount of channel-state information (CSI) that is available at the transmitter. In most cases, CSI can be measured/estimated only at the user terminals and must be fed back to the base station. This procedure typically constrains the amount of CSI that can be conveyed to the base station. Herein, we develop several low-complexity, as well as optimized, SDMA downlink resource-allocation schemes that are particularly suitable for systems utilizing statistical channel information and partial CSI feedback. A framework is proposed for combining statistical channel information with a class of instantaneous channel norms. It is shown that, in wide-area scenarios, the feedback of such a scalar norm provides sufficient information for the proposed resource-allocation algorithms to perform efficient SDMA beamforming (BF) and scheduling.

  • 8.
    Hammarwall, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Exploiting the spatial information provided by channel statistics and SNR feedback2006In: 2006 IEEE 7th Workshop on Signal Processing Advances in Wireless Communications, NEW YORK: IEEE , 2006, p. 164-168Conference paper (Refereed)
    Abstract [en]

    A major limiting factor in communication systems utilizing multiantenna transmission is the amount of spatial channel information available at the transmitter. Since the channel realizations, in most cases, can only be estimated at the receiver, such information must be fed back to the transmitter. In multiuser systems the amount of feedback must be kept minimal, which seriously limits the information that can be fed back. Herein it is shown that the feedback of a scalar signal to noise ratio (SNR), together with knowledge of the statistical properties of the channel, provides substantial spatial information about the current channel realization. The spatial information is particularly good for strong channel realizations, i.e. for users that are candidates for scheduling. Previous results are extended to the Ricean channel model and the impact of the non-zero expected value is shown to further improve the spatial information.

  • 9.
    Hammarwall, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Spatial transmit processing using long-term channel statistics and pilot signaling on selected antennas2006In: 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006, p. 762-766Conference paper (Refereed)
    Abstract [en]

    In wireless high performance systems utilizing smart antenna transmission techniques, increased pilot signaling becomes problematic when more transmit antennas are added. Herein, we propose a scheme where the pilot signaling is restricted to a subset of the transmit antennas, and the total signal strength of these antennas is fed back to the transmitter. This potentially reduces the required pilot signaling and feedback so it becomes comparable to that of single antenna systems. By combining the feedback with channel statistics, known to the transmitter, substantial spatial information is gained. Herein, this information is used to develop elaborate scheduling and beamforming techniques.

  • 10.
    Jorswieck, Eduard A.
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Hammarwall, David
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ergodic capacity achieving transmit strategy in MIMO systems with statistical and short-term norm CSI2007In: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE , 2007, p. 393-396Conference paper (Refereed)
    Abstract [en]

    The type and quality of the channel state information at the transmitter of a fading multiple-input multiple-output system greatly affects the ergodic capacity of the wireless link. In order to compare and unify the different proposals of transmit strategies for different scenarios, recently classes of MIMO channels are introduced that share a common optimal transmit strategy. In this work, we derive the ergodic capacity achieving transmit strategy for the class of unitary invariant norm feedback which complements statistical channel information at the transmitter. The impact of the short-term feedback quality is illustrated by the beamforming optimality range. The higher the feedback norm is the more likely is single stream beamforming to be optimal.

  • 11.
    Samuelsson, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    An efficient algorithm for solving the downlink beamforming problem with indefinite constraints2005In: 2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING,VOLS 1-5: SPEECH PROCESSING, IEEE , 2005, p. 905-908Conference paper (Refereed)
    Abstract [en]

    By imposing additional constraints in the downlink beamforming optimization. more general Quality of Service (QoS) measures than the average Signal to Interference and Noise Ratio (SINR) alone, can be introduced. Herein a rapidly converging algorithm solving the downlink beamforming problem with additional indefinite quadratic constraints on the beamforming vector is presented. The proposed algorithm is significantly faster than the previously proposed solution, which involves semidefinite programming. Also, the algorithm is easy to implement, since it only involves eigenvalue problems.

  • 12.
    Samuelsson, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Improved Multi user Diversity Using Smart Antennas with Limited Feedback2005In: Proceedings European Signal Processing Conference, EUSIPCO 2005, 2005, p. 1359-1362Conference paper (Refereed)
    Abstract [en]

    Multiuser divversity and beamforming are two techniques that promise dramatically increased system throughput and spectral ef- ficiency. In most systems it has however been considered infeasible to utilize spatial channel information, due to the increased feedback load. In order to exploit the benefits of both multiuser divversity and beamforming, we show how to compute the second order channel statistics, conditioned on the norm of the current channel realization. The conditional channel statistics allow for elaborate scheduling and smart antenna techniques, with limited feedback. Herein, the downlink of a single cell multiple-input singleoutput (MISO) system is considered. Only the current signal to noise ratio (SNR) is fed back from the mobile stations, whereas the second order channel statistics can be estimated at the base station from information collected in the uplink. A simple scheduling/eigenbeamforming scheme is proposed and shown to outperform opportunistic beamforming, which is a technique with similar feedback.

  • 13.
    Samuelsson, David
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Bengtsson, Mats
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Optimal downlink beamforming with additional constraints2003In: CONFERENCE RECORD OF THE THIRTY-SEVENTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, 2003, p. 1811-1814Conference paper (Refereed)
    Abstract [en]

    This work addresses the problem of joint downlink beamforming and power control with general Quality of Service (QoS) constraints. Previous work on downlink beamforming does not provide a framework to handle the additional constraints in a straightforward fashion. Herein, it is shown that the QoS requirements can be formulated as quadratic constraints to a convex optimization problem. An efficient algorithm for solving the problem, based on semidefinite optimization is presented. To demonstrate the performance of the proposed approach, we present an example using quadratic constraints to greatly decrease the probability of a low instantaneous Signal to Interference and Noise Ratio (SINR) for a receiver equipped with a RAKE combiner.

  • 14.
    Samuelsson, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Zetterberg, Per
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Realization of a spatially multiplexed MIMO system2006In: EURASTP journal an applied signal processing, ISSN 1110-8657, E-ISSN 1687-0433, Vol. 2006, p. 78349-Article in journal (Refereed)
    Abstract [en]

    Multi-antenna systems can provide improvements in wireless systems increasing spectral efficiency, reliability, range, and system capacity. Herein we show how some of the potentials of MIMO systems can be realized on a simple radio hardware platform by utilizing advanced real-time signal processing and coding. We present a real-time implementation of a 2 by 2 MIMO system employing spatial multiplexing to achieve high spectral efficiency in an indoor non-line-of-sight environment operating in the 1800 MHz range. Well-known processing and coding techniques are employed and our contributions lie in: discussing implementational aspects and solutions often overlooked but critical for high-performance operation; demonstrating the degree to which the simple baseband AWGN model can be used to accurately model/predict the MIMO system on the current hardware; and demonstrating the feasibility of real-time spatial multiplexing achieving up to 15 bps/Hz on a 2 by 2 system in a realistic indoor environment with off-the-shelf radio hardware.

  • 15.
    Svedman, Patrick
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Hammarwall, David
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Sub-carrier SNR Estimation at the Transmitter for Reduced Feedback OFDMA2006In: Proceedings European Signal Processing Conference, 2006Conference paper (Refereed)
    Abstract [en]

    In multiuser OFDMA FDD systems with resource allocation based on the instantaneous channel quality of the users, the feedback overhead can be very large. In this paper, a method to significantly reduce this feedback is proposed. The idea is to let the users feed back the channel quality (the SNR in this paper) of only a sub-set of their strongest sub-carriers. The SNRs on the other sub-carriers are instead estimated from the fed back values. We derive the MMSE estimator of the SNR of a sub-carrier, which uses two fed back SNRs as input. As a comparison, we also study the performance of the LMMSE estimator as well as spline interpolation. Numerical results show that the LMMSE estimator tends to underestimate the SNR compared to the other two estimators, whereas the interpolation tends to overestimate the SNR. System simulations including adaptive modulation and packet losses indicate that the MMSE estimator is the best choice in practice.

  • 16.
    Zetterberg, Per
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Lundin, Henrik
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Samuelsson, David
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Svedman, Patrick
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Zhang, Xi
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Implementation of SM and RxTxIR on a DSP-Based Wireless MIMO Test-Bed2004In: Proceedings of the European DSP Education and Research Symposium EDERS, 2004Conference paper (Refereed)
    Abstract [en]

    In this paper we describe the implementation of two smart-antenna strategies and associated signal processing algorithms on a common DSP-based wireless MIMO test-bed. The test-bed supports single cell and two-cell configurations. All nodes (MS andBS) have two antennas (either two transmit or tworeceive) and there are feedback links (via cable) from the receivers to all transmitters.These possibilities has been utilized differently in the two techniques: spatial multiplexing (SM) and joint receiver transmitter and interference rejection (RxTxIR).The SM technique targets a single-link low-mobility scenario and boosts throughput using two parallel spatially multiplexed modulation streams. The RxTxIR scheme utilizes the two-cell configuration of the testbed to demonstrate the possibility of suppressing intercell interference in transmitter as well as the receiver beamforming.

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