170 research outputs found

    Integrating millimeter wave with hybrid precoding multiuser massive MIMO for 5G communication

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    Nowadays, there has been growing interest in the Massive MIMO as a result of improving throughput by leveraging spatial freedom and array gain. It is equipped with millimeter wave (mm Wave) bands to resolve the high path-loss. It is known from the literature that iterated algorithms are usually used to attain the hybrid precoders to accomplish a specific optimization objective. Thus, the complexity remains high because each iteration may include singular value decomposition, the matrix inversion, and so on that motivates us to split the hybrid precoding and combining problem into sub-problems. The proposed solution is a multi-user Massive MIMO hybrid beamforming based on a convex optimization problem that is applied and solved for estimating the digital precoding to eliminate inter-user interference while using codebooks to select analog beamformers. It is apparent in the majority of cases; the proposed beamforming performance is higher than only-analog beamforming, single-user (no interference), the ZF precoding, the MMSE precoding, and the Kalman precoding where the full digital solution is a considerable as the benchmark point with different scenarios due to the reduction of user interference. Thus, there is no consideration for complicated operations such as SVD or inversion matrices as well as no need for data estimation. Our proposed solution can serve a large number of users simultaneously due to more directive gain by using numerous antennas at BS. Based on its less complexity and keeping performance, our solution can be recommended

    A Kalman Based Hybrid Precoding for Multi-User Millimeter Wave MIMO Systems

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    Millimeter-wave communication in the 60-GHz band requires large antenna arrays at both the transmit and receive terminals to achieve beamforming gains, in order to counteract the high pathloss. Fully digital techniques are infeasible with large antenna arrays due to hardware constraints at such frequencies, while purely analog solutions suffer severe performance limitations. Hybrid analog/digital beamforming is a promising solution, especially, when extended to a multi-user scenario. This paper conveys three main contributions: 1) a Kalman-based formulation for hybrid analog/digital precoding in multi-user environment is proposed; 2) an analytical expression of the error between the transmitted and estimated data is formulated, so that the Kalman algorithm at the base station does not require information on the estimated data at the mobile stations, and instead, relies only on the precoding/combining matrix; and 3) an iterative solution is designed for the hybrid precoding scheme with affordable complexity. Simulation results confirm significant improvement of the proposed approach in terms of both bit error rate and spectral efficiency–achieving almost 7 b/s/Hz, at 20 dB with 10 channel paths with respect to the analog-only beamsteering, and almost 1 b/s/Hz with respect to the hybrid minimum mean square error precoding under the same conditions

    Beamspace Aware Adaptive Channel Estimation for Single-Carrier Time-varying Massive MIMO Channels

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    In this paper, the problem of sequential beam construction and adaptive channel estimation based on reduced rank (RR) Kalman filtering for frequency-selective massive multiple-input multiple-output (MIMO) systems employing single-carrier (SC) in time division duplex (TDD) mode are considered. In two-stage beamforming, a new algorithm for statistical pre-beamformer design is proposed for spatially correlated time-varying wideband MIMO channels under the assumption that the channel is a stationary Gauss-Markov random process. The proposed algorithm yields a nearly optimal pre-beamformer whose beam pattern is designed sequentially with low complexity by taking the user-grouping into account, and exploiting the properties of Kalman filtering and associated prediction error covariance matrices. The resulting design, based on the second order statistical properties of the channel, generates beamspace on which the RR Kalman estimator can be realized as accurately as possible. It is observed that the adaptive channel estimation technique together with the proposed sequential beamspace construction shows remarkable robustness to the pilot interference. This comes with significant reduction in both pilot overhead and dimension of the pre-beamformer lowering both hardware complexity and power consumption.Comment: 7 pages, 3 figures, accepted by IEEE ICC 2017 Wireless Communications Symposiu

    Low complexity hybrid precoding designs for multiuser mmWave/THz ultra massive MIMO Systems

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    Millimeter-wave and terahertz technologies have been attracting attention from the wireless research community since they can offer large underutilized bandwidths which can enable the support of ultra-high-speed connections in future wireless communication systems. While the high signal attenuation occurring at these frequencies requires the adoption of very large (or the so-called ultra-massive) antenna arrays, in order to accomplish low complexity and low power consumption, hybrid analog/digital designs must be adopted. In this paper we present a hybrid design algorithm suitable for both mmWave and THz multiuser multiple-input multiple-output (MIMO) systems, which comprises separate computation steps for the digital precoder, analog precoder and multiuser interference mitigation. The design can also incorporate different analog architectures such as phase shifters, switches and inverters, antenna selection and so on. Furthermore, it is also applicable for different structures, namely fully-connected structures, arrays of subarrays (AoSA) and dynamic arrays of subarrays (DAoSA), making it suitable for the support of ultra-massive MIMO (UM-MIMO) in severely hardware constrained THz systems. We will show that, by using the proposed approach, it is possible to achieve good trade-offs between spectral efficiency and simplified implementation, even as the number of users and data streams increases.info:eu-repo/semantics/publishedVersio

    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
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