124 research outputs found

    Achievable Throughput of Multi-mode Multiuser MIMO with Imperfect CSI Constraints

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    For the multiple-input multiple-output (MIMO) broadcast channel with imperfect channel state information (CSI), neither the capacity nor the optimal transmission technique have been fully discovered. In this paper, we derive achievable ergodic rates for a MIMO fading broadcast channel when CSI is delayed and quantized. It is shown that we should not support too many users with spatial division multiplexing due to the residual inter-user interference caused by imperfect CSI. Based on the derived achievable rates, we propose a multi-mode transmission strategy to maximize the throughput, which adaptively adjusts the number of active users based on the channel statistics information.Comment: 5 pages, 3 figures, submitted to 2009 IEEE International Symposium on Information Theor

    Multi-mode Transmission for the MIMO Broadcast Channel with Imperfect Channel State Information

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    This paper proposes an adaptive multi-mode transmission strategy to improve the spectral efficiency achieved in the multiple-input multiple-output (MIMO) broadcast channel with delayed and quantized channel state information. The adaptive strategy adjusts the number of active users, denoted as the transmission mode, to balance transmit array gain, spatial division multiplexing gain, and residual inter-user interference. Accurate closed-form approximations are derived for the achievable rates for different modes, which help identify the active mode that maximizes the average sum throughput for given feedback delay and channel quantization error. The proposed transmission strategy is combined with round-robin scheduling, and is shown to provide throughput gain over single-user MIMO at moderate signal-to-noise ratio. It only requires feedback of instantaneous channel state information from a small number of users. With a feedback load constraint, the proposed algorithm provides performance close to that achieved by opportunistic scheduling with instantaneous feedback from a large number of users.Comment: 25 pages, 10 figures, submitted to IEEE Trans. Commun., March 201

    A survey on hybrid beamforming techniques in 5G : architecture and system model perspectives

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    The increasing wireless data traffic demands have driven the need to explore suitable spectrum regions for meeting the projected requirements. In the light of this, millimeter wave (mmWave) communication has received considerable attention from the research community. Typically, in fifth generation (5G) wireless networks, mmWave massive multiple-input multiple-output (MIMO) communications is realized by the hybrid transceivers which combine high dimensional analog phase shifters and power amplifiers with lower-dimensional digital signal processing units. This hybrid beamforming design reduces the cost and power consumption which is aligned with an energy-efficient design vision of 5G. In this paper, we track the progress in hybrid beamforming for massive MIMO communications in the context of system models of the hybrid transceivers' structures, the digital and analog beamforming matrices with the possible antenna configuration scenarios and the hybrid beamforming in heterogeneous wireless networks. We extend the scope of the discussion by including resource management issues in hybrid beamforming. We explore the suitability of hybrid beamforming methods, both, existing and proposed till first quarter of 2017, and identify the exciting future challenges in this domain

    Multiuser MIMO techniques with feedback

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    Kooperative Antennenanlagen haben vor kurzem einen heißen Forschungsthema geworden, da Sie deutlich höhere spektrale Effizienz als herkömmliche zelluläre Systeme versprechen. Der Gewinn wird durch die Eliminierung von Inter-Zelle Störungen (ICI) durch Koordinierung der-Antenne Übertragungen erworben. Vor kurzem, verteilte Organisation Methoden vorgeschlagen. Eine der größten Herausforderungen für das Dezentrale kooperative Antennensystem ist Kanalschätzung für den Downlink Kanal besonders wenn FDD verwendet wird. Alle zugehörigen Basisstationen im genossenschaftlichen Bereich müssen die vollständige Kanal Informationen zu Wissen, die entsprechenden precoding Gewicht Matrix zu berechnen. Diese Information ist von mobilen Stationen übertragen werden Stationen mit Uplink Ressourcen zu stützen. Wird als mehrere Basisstationen und mehreren mobilen Stationen in kooperativen Antennensysteme und jede Basisstation und Mobilstation beteiligt sind, können mit mehreren Antennen ausgestattet sein, die Anzahl der Kanal Parameter wieder gefüttert werden erwartet, groß zu sein. In dieser Arbeit wird ein effizientes Feedback Techniken der downlink Kanal Informationen sind für die Multi-user Multiple Input Multiple Output Fall vorgeschlagen, der insbesondere auf verteilte kooperative Antennensysteme zielt. Zuerst wird ein Unterraum-basiertes Kanalquantisierungsverfahren vorgeschlagen, das ein vorbestimmtes Codebuch verwendet. Ein iterativer Codebuchentwurfsalgorithmus wird vorgeschlagen, der zu einem lokalen optimalen Codebuch konvergiert. Darüber hinaus werden Feedback-Overhead-Reduktionsverfahren entwickelt, die die zeitliche Korrelation des Kanals ausnutzen. Es wird gezeigt, dass das vorgeschlagene adaptive Codebuchverfahren in Verbindung mit einem Datenkomprimierungsschema eine Leistung nahe an dem perfekten Kanalfall erzielt, was viel weniger Rückkopplungsoverhead im Vergleich zu anderen Techniken erfordert. Das auf dem Unterraum basierende Kanalquantisierungsverfahren wird erweitert, indem mehrere Antennen auf der Senderseite und/oder auf der Empfängerseite eingeführt werden, und die Leistung eines Vorcodierungs- (/Decodierungs-) Schemas mit regulierter Blockdiagonalisierung (RBD) wurde untersucht. Es wird ein kosteneffizientes Decodierungsmatrixquantisierungsverfahren vorgeschlagen, dass eine komplexe Berechnung an der Mobilstation vermeiden kann, während es nur eine leichte Verschlechterung zeigt. Die Arbeit wird abgeschlossen, indem die vorgeschlagenen Feedback-Methoden hinsichtlich ihrer Leistung, ihres erforderlichen Feedback-Overheads und ihrer Rechenkomplexität verglichen werden.Cooperative antenna systems have recently become a hot research topic, as they promise significantly higher spectral efficiency than conventional cellular systems. The gain is acquired by eliminating inter-cell interference (ICI) through coordination of the base antenna transmissions. Recently, distributed organization methods have been suggested. One of the main challenges of the distributed cooperative antenna system is channel estimation for the downlink channel especially when FDD is used. All of the associated base stations in the cooperative area need to know the full channel state information to calculate the corresponding precoding weight matrix. This information has to be transferred from mobile stations to base stations by using uplink resources. As several base stations and several mobile stations are involved in cooperative antenna systems and each base station and mobile station may be equipped with multiple antennas, the number of channel state parameters to be fed back is expected to be big. In this thesis, efficient feedback techniques of the downlink channel state information are proposed for the multi-user multiple-input multiple-output case, targeting distributed cooperative antenna systems in particular. First, a subspace based channel quantization method is proposed which employs a predefined codebook. An iterative codebook design algorithm is proposed which converges to a local optimum codebook. Furthermore, feedback overhead reduction methods are devised exploiting temporal correlation of the channel. It is shown that the proposed adaptive codebook method in conjunction with a data compression scheme achieves a performance close to the perfect channel case, requiring much less feedback overhead compared with other techniques. The subspace based channel quantization method is extended by introducing multiple antennas at the transmitter side and/or at the receiver side and the performance of a regularized block diagonalization (RBD) precoding(/decoding) scheme has been investigated as well as a zero-forcing (ZF) precoding scheme. A cost-efficient decoding matrix quantization method is proposed which can avoid a complex computation at the mobile station while showing only a slight degradation. The thesis is concluded by comparing the proposed feedback methods in terms of their performance, their required feedback overhead, and their computational complexity. The techniques that are developed in this thesis can be useful and applicable for 5G, which is envisioned to support the high granularity/resolution codebook and its efficient deployment schemes. Keywords: MU-MIMO, COOPA, limited feedback, CSI, CQ, feedback overhead reduction, Givens rotatio

    Exploitation of Robust AoA Estimation and Low Overhead Beamforming in mmWave MIMO System

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    The limited spectral resource for wireless communications and dramatic proliferation of new applications and services directly necessitate the exploitation of millimeter wave (mmWave) communications. One critical enabling technology for mmWave communications is multi-input multi-output (MIMO), which enables other important physical layer techniques, specifically beamforming and antenna array based angle of arrival (AoA) estimation. Deployment of beamforming and AoA estimation has many challenges. Significant training and feedback overhead is required for beamforming, while conventional AoA estimation methods are not fast or robust. Thus, in this thesis, new algorithms are designed for low overhead beamforming, and robust AoA estimation with significantly reduced signal samples (snapshots). The basic principle behind the proposed low overhead beamforming algorithm in time-division duplex (TDD) systems is to increase the beam serving period for the reduction of the feedback frequency. With the knowledge of location and speed of each candidate user equipment (UE), the codeword can be selected from the designed multi-pattern codebook, and the corresponding serving period can be estimated. The UEs with long serving period and low interference are selected and served simultaneously. This algorithm is proved to be effective in keeping the high data rate of conventional codebook-based beamforming, while the feedback required for codeword selection can be cut down. A fast and robust AoA estimation algorithm is proposed as the basis of the low overhead beamforming for frequency-division duplex (FDD) systems. This algorithm utilizes uplink transmission signals to estimate the real-time AoA for angle-based beamforming in environments with different signal to noise ratios (SNR). Two-step neural network models are designed for AoA estimation. Within the angular group classified by the first model, the second model further estimates AoA with high accuracy. It is proved that these AoA estimation models work well with few signal snapshots, and are robust to applications in low SNR environments. The proposed AoA estimation algorithm based beamforming generates beams without using reference signals. Therefore, the low overhead beamforming can be achieved in FDD systems. With the support of proposed algorithms, the mmWave resource can be leveraged to meet challenging requirements of new applications and services in wireless communication systems

    Adaptive Spatial Intercell Interference Cancellation in Multicell Wireless Networks

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    Downlink spatial intercell interference cancellation (ICIC) is considered for mitigating other-cell interference using multiple transmit antennas. A principle question we explore is whether it is better to do ICIC or simply standard single-cell beamforming. We explore this question analytically and show that beamforming is preferred for all users when the edge SNR (signal-to-noise ratio) is low (<0<0 dB), and ICIC is preferred when the edge SNR is high (>10>10 dB), for example in an urban setting. At medium SNR, a proposed adaptive strategy, where multiple base stations jointly select transmission strategies based on the user location, outperforms both while requiring a lower feedback rate than the pure ICIC approach. The employed metric is sum rate, which is normally a dubious metric for cellular systems, but surprisingly we show that even with this reward function the adaptive strategy also improves fairness. When the channel information is provided by limited feedback, the impact of the induced quantization error is also investigated. It is shown that ICIC with well-designed feedback strategies still provides significant throughput gain.Comment: 26 pages, submitted to IEEE J. Select. Areas Commun. special issue on Cooperative Communications in MIMO Cellular Networks, Sept. 200
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