A Spatial Consistency Model for Geometry-Based Stochastic Channels

Ademaj, Fjolla; Schwarz, Štefan; Rupp, Markus

doi:10.1109/access.2019.2958154

Cited by 42 publications

(25 citation statements)

References 24 publications

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“…The current paper proposes a bit allocation method for multi-user massive MIMO systems under a power constraint using a Mean Square Quantization Error (MSQE) minimization problem. In this paper, we explore reduced-connectivity radio frequency (RF) switching networks for reducing the analog hardware complexity and switching power losses in antenna selection (AS) systems [19][20][21]. A low-resolution ADC is developed by using quantization-aware antenna selection algorithm to evaluate the capacity performance of the multi-user massive MIMO compared with fast antenna selection and a random one.…”

Section: Introductionmentioning

confidence: 99%

Quantization-Aware Greedy Antenna Selection for Multi-User Massive Mimo Systems

Mahdi¹,

Al-Heety²,

Hamid³

et al. 2021

PIER C

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Using multiple-Input Multiple-Output (MIMO) configuration is not new in the field of wireless communication to increase the capacity of the system. This configuration is still valid to use nowadays with the modern wireless configuration such as the Fifth generation (5G). Massive MIMO is the key resource of the 5G systems due to its huge ability to increase the capacity of the network and on the other hand its ability to enhance both spectral and transmit-energy efficiency. The need for using Massive MIMO comes from the increase in using smartphones, tablets, and the rise of the Internet of Things. This increasing demand for the use of wireless applications requires networking and Internet infrastructures to meet the needs of current and future multimedia applications which massive MIMO satisfies. The key limitation of using massive MIMO is the cost of installation of these antennas and how to multiplex between them. In addition to this, the Radio Frequency (RF) links are also increased where this increase leads to high system complexity and hardware energy consumption. Because of this, reducing the required number of RF chains is essential to use by performing antenna selection which this paper aims to evaluate without significant performance loss which can be performed by employing low-resolution Analog-to-Digital Converter (ADC) to select an antenna with the best tradeoff between the additional channel gain and increase in quantization error. In this paper, Quantization-Aware Greedy Antenna Selection (QAGAS) algorithm has been proposed and compared with other antenna selection algorithms especially simple algorithms like random selection and Fast Antenna Selection (FAS) algorithm. The achieved capacity is compared with that of a very simple scheme that selects the antennas with the highest received power. The system capacity obtained from QAGAS is evaluated related to the transmit power of the Base Station (BS) and the quantization bits used in the lowresolution ADC. The simulation is also performed for a different numbers of users served by the BS and with the number of antennas at the BS. The simulation results show that the proposed algorithm indicates a potential for significant reductions of massive MIMO implementation complexity, by reducing the number of RF links and performing antenna selection using simple algorithms.

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Section: Introductionmentioning

confidence: 99%

Quantization-Aware Greedy Antenna Selection for Multi-User Massive Mimo Systems

Mahdi¹,

Al-Heety²,

Hamid³

et al. 2021

PIER C

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“…Thereby two-dimensional antenna arrays are utilized at least on one link-end (commonly, for space-reasons, at the base station/infrastructure node) to provide a directional view of the wireless channel and to enable three-dimensional beamforming; i.e., the antenna arrays allow to resolve the multipath profile of the channel in the angular (elevation and azimuth) domain and to steer beams along preferred directions. Correspondingly, directional channel models, such as, the third generation partnership project (3GPP) threedimensional channel model [21,22] or the Quadriga channel model [23], became relevant for the optimization of wireless communication systems. These channel models are powerful tools that are well-suited for generating realistic random realizations of commonly encountered propagation environments, e.g., for rural/urban outdoor/indoor scenarios, and are therefore indispensable for system evaluation.…”

Section: Introductionmentioning

confidence: 99%

Reliable Multi-Point Transmissions Over Directional MISO TWDP Fading Channels

Schwarz

Rupp

2021

IEEE Trans. Veh. Technol.

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In this paper, we consider wireless transmissions over directional multiple-input single-output (MISO) two wave with diffuse power (TWDP) fading channels, subject to interference over the same type of channel. TWDP fading is known to exhibit an outage behavior that can be even worse than Rayleigh fading and has experimentally been observed in a number of vehicular channel measurement campaigns. To enhance the reliability of multi-point transmissions over MISO TWDP fading channels, we propose a zero-forcing based coordinated beamforming scheme, for which we can analytically characterize and optimize the outage probability of the multi-point transmissions. Based on the developed outage expressions, we furthermore propose a greedy coordinated scheduling approach that attempts to maximize the achievable rate of the system. Finally, we propose a transmission rate adaptation scheme for fixed size packet transmissions, which supports reliable and at the same time resource efficient multi-point transmissions.

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“…This has been lately recognized by the Third Generation Partnership Project (3GPP), who have standardized SC modelling in Release 14 TR 38.901 [5]. Specifically, two SC procedures are proposed for modelling the continuity of channel parameters over a coherence distance of 15 m. Based on this, the authors of [6] adapted the New York University Simulator model to have a SC procedure over UE moving distances of 15 m. Further work on evaluating the 3GPP SC procedures has been reported in [7], [8] using the Quasi Deterministic Radio Channel Generator model at 2 GHz.…”

Section: Introductionmentioning

confidence: 99%

Impact of Spatially Consistent Channels on Digital Beamforming for Millimeter-Wave Systems : (Invited Paper)

Tataria

Tufvesson

2020

2020 14th European Conference on Antennas and Propagation (EuCAP)

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The premise of massive multiple-input multipleoutput (MIMO) is based around coherent transmission and detection. Majority of the vast literature on massive MIMO presents performance evaluations over simplified statistical propagation models. All such models are drop-based and do not ensure continuity of channel parameters. In this paper, we quantify the impact of spatially consistent (SC) models on beamforming for massive MIMO systems. We focus on the downlink of a 28 GHz multiuser urban microcellular scenario. Using the recently standardized Third Generation Partnership Project 38.901 SC-I procedure, we evaluate the signal-to-interference-plus-noise ratio of a user equipment and the system ergodic sum spectral efficiency with zero-forcing, block diagonalization, and signalto-leakage-plus-noise ratio beamforming. Across different user movement trajectories, our results disclose that SC channels yield a significant performance loss relative to the case without SC due to substantial spatial correlation across the channel parameters.

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A Spatial Consistency Model for Geometry-Based Stochastic Channels

Cited by 42 publications

References 24 publications

Quantization-Aware Greedy Antenna Selection for Multi-User Massive Mimo Systems

Quantization-Aware Greedy Antenna Selection for Multi-User Massive Mimo Systems

Reliable Multi-Point Transmissions Over Directional MISO TWDP Fading Channels

Impact of Spatially Consistent Channels on Digital Beamforming for Millimeter-Wave Systems : (Invited Paper)

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