scholarly journals Effects of Path Visibility on Urban MIMO Systems

1970 ◽  
Vol 5 (1) ◽  
pp. 22-30
Author(s):  
Sirichai Hemrungrote ◽  
Toshikazu Hori ◽  
Mitoshi Fujimoto ◽  
Kentaro Nishimori
Keyword(s):  
Channel Capacity ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Propagation Characteristics ◽  
Simple Method ◽  
Limited Bandwidth ◽  
Multiple Input ◽  
Input Multiple Output

Multiple-Input Multiple-Output (MIMO) wireless communication technology is expected to improve the channel capacity over the limited bandwidth of existing networks. Since urban MIMO systems have complex propagation characteristics, the channel capacity cannot be estimated using a simple method. Hence, we introduce channel capacity characteristics to urban MIMO systems by using a combination of imaging and ray-launching methods as a ray-tracing scheme. A simulation based on these methods with variable parameters can reproducibly estimate various urban propagation characteristics and discriminate the effects of the urban model and antenna configurations. The characteristics of the Signal-to-Noise Ratio (SNR), the channel capacity, the spatial correlation, as well as the path visibility are then determined from the results of the simulation. The parameter called path visibility introduced in our previous study is considered again herein. We clarify that only this single parameter can be used to determine the channel capacity characteristics in urban MIMO scenarios. This parameter also provides guidance in determining the appropriate range for the base station (BS) height.

scholarly journals Beam division multiple access for millimeter wave massive MIMO: Hybrid zero-forcing beamforming with user selection

2022 ◽  
Vol 12 (1) ◽  
pp. 445
Author(s):  
Hong Son Vu ◽  
Kien Truong ◽  
Minh Thuy Le
Keyword(s):  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Zero Forcing ◽  
Multiuser Interference ◽  
Novel Approach ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Promising Solution

<p>Massive multiple-input multiple-output (MIMO) systems are considered a promising solution to minimize multiuser interference (MUI) based on simple precoding techniques with a massive antenna array at a base station (BS). This paper presents a novel approach of beam division multiple access (BDMA) which BS transmit signals to multiusers at the same time via different beams based on hybrid beamforming and user-beam schedule. With the selection of users whose steering vectors are orthogonal to each other, interference between users is significantly improved. While, the efficiency spectrum of proposed scheme reaches to the performance of fully digital solutions, the multiuser interference is considerably reduced.</p>

scholarly journals Adaptive Threshold-Aided K-Best Sphere Decoding for Large MIMO Systems

2019 ◽  
Vol 9 (21) ◽  
pp. 4624
Author(s):  
Uzokboy Ummatov ◽  
Kyungchun Lee
Keyword(s):  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Threshold Value ◽  
Adaptive Threshold ◽  
Sphere Decoding ◽  
High Signal ◽  
Signal To Noise ◽  
Multiple Input ◽  
Input Multiple Output

This paper proposes an adaptive threshold-aided K-best sphere decoding (AKSD) algorithm for large multiple-input multiple-output systems. In the proposed scheme, to reduce the average number of visited nodes compared to the conventional K-best sphere decoding (KSD), the threshold for retaining the nodes is adaptively determined at each layer of the tree. Specifically, we calculate the adaptive threshold based on the signal-to-noise ratio and index of the layer. The ratio between the first and second smallest accumulated path metrics at each layer is also exploited to determine the threshold value. In each layer, in addition to the K paths associated with the smallest path metrics, we also retain the paths whose path metrics are within the threshold from the Kth smallest path metric. The simulation results show that the proposed AKSD provides nearly the same bit error rate performance as the conventional KSD scheme while achieving a significant reduction in the average number of visited nodes, especially at high signal-to-noise ratios.

scholarly journals Gyre Precoding and T-Transformation-Based GFDM System for UAV-Aided mMTC Network

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2915
Author(s):  
Joarder Jafor Sadique ◽  
Shaikh Enayet Ullah ◽  
Raad Raad ◽  
Md. Rabiul Islam ◽  
Md. Mahbubar Rahman ◽  
...  
Keyword(s):  
Channel Coding ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Mobility Model ◽  
Base Station ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Aerial Vehicle ◽  
Noise Ratio ◽  
User Interference

In this paper, an unmanned aerial vehicle (UAV)-aided multi-antenna configured downlink mmWave cooperative generalized frequency division multiplexing (GFDM) system is proposed. To provide physical layer security (PLS), a 3D controlled Lorenz mapping system is introduced. Furthermore, the combination of T-transformation spreading codes, walsh Hadamard transform, and discrete Fourier transform (DFT) techniques are integrated with a novel linear multi-user multiple-input multiple-output (MU-MIMO) gyre precoding (GP) for multi-user interference reduction. Furthermore, concatenated channel-coding with multi-user beamforming weighting-aided maximum-likelihood and zero forcing (ZF) signal detection schemes for an improved bit error rate (BER) are also used. The system is then simulated with a single base station (BS), eight massive machine-type communications (mMTC) users, and two UAV relay stations (RSs). Numerical results reveal the robustness of the proposed system in terms of PLS and an achievable ergodic rate with signal-to-interference-plus-noise ratio (SINR) under the implementation of T-transformation scheme. By incorporating the 3D mobility model, brownian perturbations of the UAVs are also analyzed. An out-of-band (OOB) reduction of 320 dB with an improved BER of 1×10−4 in 16-QAM for a signal-to-noise ratio, Eb/N0, of 20 dB is achieved.

scholarly journals Spectral Efficiency Improvement Techniques In Massive Mimo For 5G Communications

2021 ◽  
Vol 12 (2) ◽  
pp. 1457-1465
Author(s):  
Naraiah R , Et. al.
Keyword(s):  
Spectral Efficiency ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Broad Band ◽  
Cell System ◽  
Base Station ◽  
Information Rate ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Long Time

Wireless communications has gotten one of the quickest developing zones in our advanced life and makes colossal effect on practically every component of our day by day life. 5G should support a large number of new applications with a wide assortment of prerequisites, including higher pinnacle and client information rates, diminished dormancy, improved indoor inclusion, expanded number of gadgets, etc. The normal traffic development in at least a long time from now can be fulfilled by the consolidated utilization of more range, higher spectral efficiency, and densification of cells. The increment in spectral effectiveness will improve the throughput of the system which straightforwardly serves the Enhanced Mobile Broad band use instance of the 5G assistance. In massive Multiple-Input Multiple-Output (M-MIMO) systems few hundred quantities of antennas are conveyed at each base station (BS) to serve a moderately modest number of single-reception apparatus terminals with multiuser, giving higher information rate and lower idleness. Massive Multiple-Input Multiple-Output is the arising innovation in cell system for higher information rate correspondence. It utilizes enormous number of communicating reception apparatus at the base station which is made conceivable by the radio wire cluster which can be electronically steerable and adequately utilized for shaft framing. Spectral proficiency is the vital boundary to be improved in expanding throughput. The system execution under different commonsense limitations and conditions, for example, restricted soundness block length, number of base station (BS) antennas, and number of dynamic clients are assessed through simulation.  

scholarly journals Sectoral dual-polarized MIMO antenna for 5G-NR band N77 base station

2021 ◽  
Vol 21 (3) ◽  
pp. 1611
Author(s):  
Muhsin Muhsin ◽  
Afina Lina Nurlaili ◽  
Aulia Saharani ◽  
Indah Rahmawti Utami
Keyword(s):  
High Performance ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Mimo Antenna ◽  
Future Technology ◽  
New Radio ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Dual Polarized

<span>Massive internet of things (IoT) in 5G has many advantages as a future technology. It brings some challenges such as a lot of devices need massive connection. In this case, multiple-input multiple-output (MIMO) systems offer high performance and capacity of communications. There is a challenge of correlation between antennas in MIMO. 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. The proposed antenna has a maximum coupling of -16.90 dB and correlation below 0.01. The obtained bit error rate (BER) performance is very close to non-correlated antennas with bandwidth of 1.87 GHz. It means that the proposed antenna has been well designed.</span>

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer ◽  
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

scholarly journals Effective Power Allocation Using for Transmit Source In MIMO Relay Communication

2021 ◽  
Vol 5 (3) ◽  
Author(s):  
Hoai Trung Tran
Keyword(s):  
Channel Capacity ◽  
Communication Systems ◽  
High Speed ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Optimization Method ◽  
Radio Communication ◽  
Second Derivatives ◽  
Multiple Input ◽  
Input Multiple Output

The Multiple Input Multiple Output (MIMO) systems using relays are of interest for high-speed radio communication systems. Currently, most of the articles are interested in the model of three nodes with purposes such as increasing the channel capacities (mutual information) or reducing the minimum mean square of error. This paper extends to more than one relay and is concerned with the maximum channel capacity. It is assumed that the channel matrices between source and relay as well as relay and receiver are random matrices; the relay precoders are also assumed to be random and known at the receiver. The article proposes that the Lagrange multiplier finding algorithm using the Newton – Raphson optimization method is more straightforward than the traditional finding algorithm using the first and second derivatives but still gives a higher channel capacity.

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

A Comparison of Norm Based Antenna Selection and Random Antenna Selection with Regard to Energy Efficiency in Wireless System with Large Number of Users

2020 ◽  
Vol 10 (2) ◽  
pp. 189-196
Author(s):  
Ashu Taneja ◽  
Nitin Saluja
Keyword(s):  
Energy Efficiency ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Transmit Antenna Selection ◽  
Wireless System ◽  
Multiple Input ◽  
Input Multiple Output

Background: The paper considers the wireless system with large number of users (more than 50 users) and each user is assigned large number of antennas (around 200) at the Base Station (BS). Objective: The challenges associated with the defined system are increased power consumption and high complexity of associated circuitry. The antenna selection is introduced to combat these problems while the usage of linear precoding reduces computational complexity. The literature suggests number of antenna selection techniques based on statistical properties of signal. However, each antenna selection technique suits well to specific number of users. Methods: In this paper, the random antenna selection is compared with norm-based antenna selection. It is analysed that the random antenna selection leads to inefficient spectral efficiency if the number of users are more than 50 in Multi-User Multiple-Input Multiple Output (MU-MIMO) system. Results: The paper proposes the optimization of Energy-Efficiency (EE) with random transmit antenna selection for large number of users in MU-MIMO systems. Conclusion: Also the computation leads to optimization of number of transmit antennas at the BS for energy efficiency. The proposed algorithm results in improvement of the energy efficiency by 27% for more than 50 users.

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