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These attractive features make this array an ideal candidate for further 5G massive MIMO base station antenna developments.

A Low-Profile Dual-Band Dual-Polarized Base Station Antenna Array for Sub-6 GHz Applications

attractive features make

These attractive features make this array an ideal candidate for future 5G massive MIMO base station antenna developments.

Decoupling and Low-Profile Design of Dual-Band Dual-Polarized Base Station Antennas Using Frequency-Selective Surface

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Mimo Base sentence examples within Massive Mimo Base

Massive Mimo Base

To this end, we investigate the rate performance of a system employing multi-user NOMA and massive MIMO base stations distributed under a Poisson process.

Rate and Energy Efficiency Improvements of Massive MIMO-Based Stochastic Cellular Networks With NOMA

Massive Mimo Base

In the coherence interval based pilot setting, by extensive system level simulations, we find that using a Massive MIMO base station with 128 antennas and MMSE receiver, URLLC requirements can be achieved in Urban Macro (UMa) Non-Line of Sight (NLoS) with orthogonal pilots and Neyman-Pearson detector.

Can Massive MIMO Support URLLC?

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mimo base station

, disabling some of the antennas installed at a 5G MMIMO Base Station (BS) when there are few User Equipments (UEs) within the cell area.

Reinforcement Learning for Energy-Efficient 5G Massive MIMO: Intelligent Antenna Switching

mimo base station

To this end, we investigate the rate performance of a system employing multi-user NOMA and massive MIMO base stations distributed under a Poisson process.

Rate and Energy Efficiency Improvements of Massive MIMO-Based Stochastic Cellular Networks With NOMA

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10.1007/S11276-017-1614-Y

In this paper, we propose a carrier sensing based MAC protocol for a MU-MIMO based WLAN with full utilization of MU-MIMO technique.

Saturation throughput analysis of a carrier sensing based MU-MIMO MAC protocol in a WLAN under fading and shadowing

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10.1109/WCNC.2019.8886103

We consider both single user (SU) and multiuser (MU) reception modes of a millimeter-Wave (mmWave) massive-MIMO base station (BS).

Robust Hybrid Analog/Digital Beamforming for Uplink Massive-MIMO with Imperfect CSI

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10.1016/J.AEUE.2019.01.028

Results reveal that MIMO based hybrid system significantly improves BER performance with approximately same PAPR compared to that of hybrid system.

Performance analysis of Selective Mapping and clipping based multicarrier-CDMA system with and without MIMO technique

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10.1109/ICIIP47207.2019.8985852

In this paper, we have exploited the key technologies of the next generation communication systems which are cognitive radio (CR), non-orthogonal multiple access (NOMA) and multiple-input-multiple-output (MIMO) and have proposed a framework of simultaneous use of these technologies for the spectral efficient design, named as MIMO based CR-NOMA communication systems.

Sum-Rate Analysis of MIMO Based CR-NOMA Communication System

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10.1109/JSAC.2019.2947941

To overcome the above problems, in this paper we propose heterogeneous statistical-QoS driven resource allocation policies for mmWave m-MIMO based 5G wireless networks in both asymptotic and non-asymptotic regimes.

Heterogeneous Statistical-QoS Driven Resource Allocation Over mmWave Massive-MIMO Based 5G Mobile Wireless Networks in the Non-Asymptotic Regime

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10.1007/S10043-019-00537-Z

In this paper, we develop a comparison between MIMO over multimode fiber (MMF) using MGDM and MIMO based FSO links.

Comparative analysis of MIMO-based FSO and MIMO-based MGDM communications

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10.1109/TSC.2019.2892428

In this paper, we study the computation task offloading and resource allocation optimization in MIMO based mobile edge computing systems considering perfect/imperfect-CSI estimation.

Computation Offloading in MIMO Based Mobile Edge Computing Systems Under Perfect and Imperfect CSI Estimation

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10.1109/TAP.2019.2922541

In this study, we have evaluated the proposed antenna as a MIMO base station antenna and characterized it in two different propagation scenarios.

Characterization and Performance of an Ultra-Wideband Wide-Coverage Multimode MIMO Antenna

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10.1109/IBSSC47189.2019.8973073

MIMO based antenna has been proposed for diversity reception along with compact size and futuristic aesthetic design.

Smart Antenna Design And Implementation For Vehicles

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10.1109/SPAWC.2019.8815575

We investigate the interfering channel estimation in radar and communication coexistence, where a multi-input-multi-output (MIMO) radar is operated in a “search and track” mode, and a MIMO base station (BS) is attempting to acquire the interfering channel state information (ICSI) between them, which is required for the precoding designs.

Interfering Channel Estimation for Radar and Communication Coexistence

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10.1109/ISCAS.2019.8702740

Typical massive MU-MIMO base-station (BS) designs rely on centralized linear data detectors and precoders which entail excessively high complexity, interconnect data rates, and chip input/output (I/O) bandwidth when executed on a single computing fabric.

Decentralized Coordinate-Descent Data Detection and Precoding for Massive MU-MIMO

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10.1007/S11277-019-06179-3

Femtocell base stations bid for a channel with pricing value to the MIMO base station spectrum manager and the spectrum manager allocates spectrum to the femtocell base station based on maximum pricing value.

Energy and Spectrum Optimization for 5G Massive MIMO Cognitive Femtocell Based Mobile Network Using Auction Game Theory

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10.1109/COMNETSAT.2019.8844099

Using the FPGA implementation on the SIMO channel, the design can be extended to the hardware of spatially modulated hyper-MIMO based 5th generation networks.

FPGA Design of Spatially Modulated Single-Input-Multiple-Output Signals in 5G Diversity Receivers

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Mimo Base
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What is/are Mimo Base?

Mimo Base - In this paper, we propose a carrier sensing based MAC protocol for a MU-MIMO based WLAN with full utilization of MU-MIMO technique. [1] We consider both single user (SU) and multiuser (MU) reception modes of a millimeter-Wave (mmWave) massive-MIMO base station (BS). [2] Results reveal that MIMO based hybrid system significantly improves BER performance with approximately same PAPR compared to that of hybrid system. [3] In this paper, we have exploited the key technologies of the next generation communication systems which are cognitive radio (CR), non-orthogonal multiple access (NOMA) and multiple-input-multiple-output (MIMO) and have proposed a framework of simultaneous use of these technologies for the spectral efficient design, named as MIMO based CR-NOMA communication systems. [4] To overcome the above problems, in this paper we propose heterogeneous statistical-QoS driven resource allocation policies for mmWave m-MIMO based 5G wireless networks in both asymptotic and non-asymptotic regimes. [5] In this paper, we develop a comparison between MIMO over multimode fiber (MMF) using MGDM and MIMO based FSO links. [6] In this paper, we study the computation task offloading and resource allocation optimization in MIMO based mobile edge computing systems considering perfect/imperfect-CSI estimation. [7] In this study, we have evaluated the proposed antenna as a MIMO base station antenna and characterized it in two different propagation scenarios. [8] MIMO based antenna has been proposed for diversity reception along with compact size and futuristic aesthetic design. [9] We investigate the interfering channel estimation in radar and communication coexistence, where a multi-input-multi-output (MIMO) radar is operated in a “search and track” mode, and a MIMO base station (BS) is attempting to acquire the interfering channel state information (ICSI) between them, which is required for the precoding designs. [10] Typical massive MU-MIMO base-station (BS) designs rely on centralized linear data detectors and precoders which entail excessively high complexity, interconnect data rates, and chip input/output (I/O) bandwidth when executed on a single computing fabric. [11] Femtocell base stations bid for a channel with pricing value to the MIMO base station spectrum manager and the spectrum manager allocates spectrum to the femtocell base station based on maximum pricing value. [12] Using the FPGA implementation on the SIMO channel, the design can be extended to the hardware of spatially modulated hyper-MIMO based 5th generation networks. [13]

attractive features make

These attractive features make this array an ideal candidate for further 5G massive MIMO base station antenna developments. [1] These attractive features make this array an ideal candidate for future 5G massive MIMO base station antenna developments. [2] These attractive features make this array an ideal candidate for further 5G massive MIMO base station antenna developments. [3]

Massive Mimo Base

To this end, we investigate the rate performance of a system employing multi-user NOMA and massive MIMO base stations distributed under a Poisson process. [1] In the coherence interval based pilot setting, by extensive system level simulations, we find that using a Massive MIMO base station with 128 antennas and MMSE receiver, URLLC requirements can be achieved in Urban Macro (UMa) Non-Line of Sight (NLoS) with orthogonal pilots and Neyman-Pearson detector. [2] In this paper, we develop and evaluate compressed representations of the channels between a massive MIMO base station and user terminals that can serve as attractive proxies in the context of various applications of interest. [3] Mobile phone operators have begun the roll-out of 5G networks, deploying massive MIMO base stations. [4] Current extrapolation procedures for the assessment of theoretical maximum RF-EMF exposure to 5G massive MIMO base stations consider the antenna gain difference between SSB and traffic beams. [5] In the proposed approach, the fingerprints rely solely on the RSS from the single-antenna MT collected at each of the receive antenna elements of the massive MIMO base station. [6] In Massive MIMO base stations (BSs), the hardware design needs to balance high spectral efficiency (SE) with low complexity. [7] The spatial spectrum of the incoherent narrowband uplink pilot signal on each frequency bin received at the distributed massive MIMO base stations (BSs) is used for spectrum fusion. [8] Massive MIMO base stations are expensive to build due to the requirement for a large number of RF transceivers and high-resolution analog-to-digital converters. [9] This paper proposes a circularly polarized 1 × 4 antenna array with improved Isolation for Massive MIMO Base Station application. [10] Aiming the implementation of green Cell-Free massive MIMO system based on radio stripe, we propose Random AP Switch ON/OFF(RAPSO) framework for switching off APs in Cell-Free massive MIMO based on radio stripe. [11] We first show that the performance of massive MIMO based grant-free random access is mainly decided by the probability of preamble collision. [12] The measurements were conducted using a massive MIMO base station (BS) testbed and virtual arrays of receivers, positioned with a robotic system. [13] In this paper, we study the problem of user activity detection and large-scale fading coefficient estimation in a random access wireless uplink with a massive MIMO base station with a large number $M$ of antennas and a large number of wireless single-antenna devices (users). [14] In this paper, we analyze the energy-efficiency of the quantized Zero-Forcing precoded systems for a large number of users and a massive MIMO base station. [15] It can find good application scenarios in both mobile terminals and Massive MIMO base stations of 5G wireless communication systems. [16] The massive MIMO base station exploits the available uplink CSI to help recovering the unknown downlink CSI from low rate user feedback. [17] In this paper, the joint communication and computation resource allocation problem for a single cell massive MIMO based mobile edge computing (MEC) network is discussed. [18] A downlink user scheduling algorithm based on the pricing scheduling factor is proposed for the established relay-assisted massive multiple input multiple output (MIMO) model, which represents the typical remote cell with multiple relays and a massive MIMO base station. [19] These attractive features make this array an ideal candidate for further 5G massive MIMO base station antenna developments. [20] These attractive features make this array an ideal candidate for future 5G massive MIMO base station antenna developments. [21] In this paper, modeling content popularity as a finite state Markov chain, reinforcement Q-learning is employed to learn optimal content placement strategy to maximize the average success probability (ASP) in homogeneous Poisson point process (PPP) distributed caching network having massive MIMO base stations. [22] These attractive features make this array an ideal candidate for further 5G massive MIMO base station antenna developments. [23] A dual-polarized dual-dipole antenna with low mutual coupling for massive MIMO base stations is proposed. [24] This is because FD communication at mmWave frequencies needs to be able to deal with fast phase noise (PN) variation, and FD massive MIMO base station (BS) requires simultaneous cancellation of SI and multi-user interference (MUI). [25] Rectangular antenna arrays, associated with 32 to 64 transceivers, are the most commonly-considered configurations for massive MIMO base stations. [26] This paper considers a hybrid two-step space-frequency receiver structure for multiuser uplink millimeter-wave (mmWave) massive MIMO based systems. [27] This work investigates the performance of spectral efficiency (SE) of the massive MIMO based on the finite-dimensional physical channel model instead of conventional i. [28] It is assumed that a massive MIMO base station with 64 compact antennas with sub-wavelength spacing (0. [29] In this paper, we proposes a uplink channel estimation scheme where a sub-connected hybrid massive MIMO base station (BS) communicates with a single-antenna user. [30] We consider the problem of unsourced random access (U-RA), a grant-free uncoordinated form of random access, in a wireless channel with a massive MIMO base station equipped with a large number M of antennas and a large number of wireless single-antenna devices (users). [31] In this paper, we consider an underlay radar- massive MIMO spectrum sharing scenario in which massive MIMO base stations (BSs) with elevation beamforming capabilities are allowed to operate outside a circular exclusion zone centered at the radar. [32] A practically realizable generalized likelihood ratio test (GLRT) is formulated when the eavesdropper's signal parameters are unknown to the massive MIMO base-station. [33] The excess degrees-of-freedom offered by a massive MIMO base-station (BS) are exploited for sending artificial noise (AN) via random and null-space precoders. [34] These experimental data confirms that, the output power from massive MIMO base stations is spatially distributed and that assuming constant peak power transmission in a fixed direction leads to unrealistic exposure values. [35] A low-dimensional digital precoder is cascaded with a high-dimensional analog precoder and thus reducing the number of RF chains required at the NOMA-enabled massive MIMO base-station. [36] The uplink channels are estimated at the massive MIMO base-station (BS) by using the pilots transmitted by the user nodes in all clusters. [37] The network consists of a massive MIMO base station (BS) and two groups of single- antenna sensor nodes which harvest energy from the BS. [38] Two types of wire-grid FSS, in the form of wall and screen are considered in the vicinity of a 64-element massive MIMO base- station (BS) array, serving a cluster of four fixed user equipments (UEs). [39] Finally, Security protocols based on network demands are implemented through AI in D2D Communications of Massive MIMO based 5G Networks. [40] We apply it to estimate the exposure in a model of an industrial indoor environment with a single massive MIMO base station (BS). [41]

mimo base station

, disabling some of the antennas installed at a 5G MMIMO Base Station (BS) when there are few User Equipments (UEs) within the cell area. [1] To this end, we investigate the rate performance of a system employing multi-user NOMA and massive MIMO base stations distributed under a Poisson process. [2] In the coherence interval based pilot setting, by extensive system level simulations, we find that using a Massive MIMO base station with 128 antennas and MMSE receiver, URLLC requirements can be achieved in Urban Macro (UMa) Non-Line of Sight (NLoS) with orthogonal pilots and Neyman-Pearson detector. [3] In this paper, we develop and evaluate compressed representations of the channels between a massive MIMO base station and user terminals that can serve as attractive proxies in the context of various applications of interest. [4] Mobile phone operators have begun the roll-out of 5G networks, deploying massive MIMO base stations. [5] Current extrapolation procedures for the assessment of theoretical maximum RF-EMF exposure to 5G massive MIMO base stations consider the antenna gain difference between SSB and traffic beams. [6] In the proposed approach, the fingerprints rely solely on the RSS from the single-antenna MT collected at each of the receive antenna elements of the massive MIMO base station. [7] In Massive MIMO base stations (BSs), the hardware design needs to balance high spectral efficiency (SE) with low complexity. [8] The spatial spectrum of the incoherent narrowband uplink pilot signal on each frequency bin received at the distributed massive MIMO base stations (BSs) is used for spectrum fusion. [9] Massive MIMO base stations are expensive to build due to the requirement for a large number of RF transceivers and high-resolution analog-to-digital converters. [10] This paper proposes a circularly polarized 1 × 4 antenna array with improved Isolation for Massive MIMO Base Station application. [11] The roll-out of the 5G standard with novel functionalities brings with it the urgent need to evaluate the human exposure to massive-MIMO base stations. [12] An electromagnetic transparent antenna element is proposed for dual-band shared-aperture fifth-generation (5G) MIMO base station antenna array developments. [13] The measurements were conducted using a massive MIMO base station (BS) testbed and virtual arrays of receivers, positioned with a robotic system. [14] In this paper, we study the problem of user activity detection and large-scale fading coefficient estimation in a random access wireless uplink with a massive MIMO base station with a large number $M$ of antennas and a large number of wireless single-antenna devices (users). [15] This paper proposes three-sectors MIMO base station antenna for 5G-New Radio (5G-NR) band N77 with dual polarized configuration to reduce the correlation. [16] In this paper, we analyze the energy-efficiency of the quantized Zero-Forcing precoded systems for a large number of users and a massive MIMO base station. [17] We consider both single user (SU) and multiuser (MU) reception modes of a millimeter-Wave (mmWave) massive-MIMO base station (BS). [18] It can find good application scenarios in both mobile terminals and Massive MIMO base stations of 5G wireless communication systems. [19] The massive MIMO base station exploits the available uplink CSI to help recovering the unknown downlink CSI from low rate user feedback. [20] A downlink user scheduling algorithm based on the pricing scheduling factor is proposed for the established relay-assisted massive multiple input multiple output (MIMO) model, which represents the typical remote cell with multiple relays and a massive MIMO base station. [21] These attractive features make this array an ideal candidate for further 5G massive MIMO base station antenna developments. [22] These attractive features make this array an ideal candidate for future 5G massive MIMO base station antenna developments. [23] In this paper, modeling content popularity as a finite state Markov chain, reinforcement Q-learning is employed to learn optimal content placement strategy to maximize the average success probability (ASP) in homogeneous Poisson point process (PPP) distributed caching network having massive MIMO base stations. [24] In enormous MIMO base station antennas will be in the order of tens or hundreds to increase streams of data confined inside the cell. [25] These attractive features make this array an ideal candidate for further 5G massive MIMO base station antenna developments. [26] A dual-polarized dual-dipole antenna with low mutual coupling for massive MIMO base stations is proposed. [27] This is because FD communication at mmWave frequencies needs to be able to deal with fast phase noise (PN) variation, and FD massive MIMO base station (BS) requires simultaneous cancellation of SI and multi-user interference (MUI). [28] Rectangular antenna arrays, associated with 32 to 64 transceivers, are the most commonly-considered configurations for massive MIMO base stations. [29] It is assumed that a massive MIMO base station with 64 compact antennas with sub-wavelength spacing (0. [30] In this paper, we proposes a uplink channel estimation scheme where a sub-connected hybrid massive MIMO base station (BS) communicates with a single-antenna user. [31] We consider the problem of unsourced random access (U-RA), a grant-free uncoordinated form of random access, in a wireless channel with a massive MIMO base station equipped with a large number M of antennas and a large number of wireless single-antenna devices (users). [32] In this study, we have evaluated the proposed antenna as a MIMO base station antenna and characterized it in two different propagation scenarios. [33] In this paper, we consider an underlay radar- massive MIMO spectrum sharing scenario in which massive MIMO base stations (BSs) with elevation beamforming capabilities are allowed to operate outside a circular exclusion zone centered at the radar. [34] We investigate the interfering channel estimation in radar and communication coexistence, where a multi-input-multi-output (MIMO) radar is operated in a “search and track” mode, and a MIMO base station (BS) is attempting to acquire the interfering channel state information (ICSI) between them, which is required for the precoding designs. [35] These experimental data confirms that, the output power from massive MIMO base stations is spatially distributed and that assuming constant peak power transmission in a fixed direction leads to unrealistic exposure values. [36] Femtocell base stations bid for a channel with pricing value to the MIMO base station spectrum manager and the spectrum manager allocates spectrum to the femtocell base station based on maximum pricing value. [37] The network consists of a massive MIMO base station (BS) and two groups of single- antenna sensor nodes which harvest energy from the BS. [38] We apply it to estimate the exposure in a model of an industrial indoor environment with a single massive MIMO base station (BS). [39]