Antenna Theory And Design

The global bandwidth shortage in the wireless communication sector has motivated the study and exploration of wireless access technology known as massive Multiple-Input Multiple-Output (MIMO). Massive MIMO is one of the key enabling technology for next-generation networks, which groups together antennas at both transmitter and the receiver to provide high spectral and energy efficiency using relatively simple processing. Obtaining a better understating of the massive MIMO system to overcome the fundamental issues of this technology is vital for the successful deployment of 5G—and beyond—networks to realize various applications of the intelligent sensing system. In this paper, we present a comprehensive overview of the key enabling technologies required for 5G and 6G networks, highlighting the massive MIMO systems. We discuss all the fundamental challenges related to pilot contamination, channel estimation, precoding, user scheduling, energy efficiency, and signal detection in a massive MIMO system and discuss some state-of-the-art mitigation techniques. We outline recent trends such as terahertz communication, ultra massive MIMO (UM-MIMO), visible light communication (VLC), machine learning, and deep learning for massive MIMO systems. Additionally, we discuss crucial open research issues that direct future research in massive MIMO systems for 5G and beyond networks.

Massive MIMO Systems for 5G and Beyond Networks-Overview, Recent Trends, Challenges, and Future Research Direction.

With an incredible increase in the number of wireless devices and an ever-growing demand for high data rates, 5G needs to provide a solution to satisfy the demand for the next decade. Multiple-input multiple-output (MIMO) systems are seen as one of the primary solutions—allowing for spatial multiplexing and the use of millimeter-wave (mmWave) frequencies, which can provide much larger bandwidths and, thus, data rates. MIMO is very closely related to phased arrays, which have been used for radar for the past few decades and requires many antennas and transceivers—on the order of hundreds or thousands for massive MIMO. To make such systems affordable, low-cost, low-power, and low-complexity is required—inherently compromising other system characteristics, such as linearity. The main focus of this paper will be in summarizing the challenges, recent advances, and potential future breakthroughs concerning MIMO/digital array sensitivity to interferers and nonlinear distortion. Specifically, this paper gives an overview of MIMO/digital array architectures and different techniques currently researched for the characterization and mitigation of spatial and spectral interferers and nonlinearities, which can be used to extend the effective dynamic range of low-cost MIMO/digital array systems.

Survey: Characterization and Mitigation of Spatial/Spectral Interferers and Transceiver Nonlinearities for 5G MIMO Systems

Millimeter Wave (mmWave) Massive Multiple Input Multiple Output (MIMO) has been a promising candidate for the current and next generation of cellular networks. The hybrid analogue/digital precoding will be a crucial ingredient in the mmWave cellular systems to reduce the number of Radio Frequency (RF) chains along with the corresponding energy and power consumption of the systems. In this paper, we aim to improve the energy efficiency of mmWave Massive MIMO by using a combination of high dimension analogue precoder and low dimension digital precoder. The spectral efficiency and the corresponding transmitted and consumed power of the mmWave Massive MIMO is formulated by taking all the consumed power from the transmitting side to receiving end into account. We propose the Power Controlled Energy Maximization (PCEM) algorithm in this paper, and the proposed algorithm works by controlling the transmission power to balance the improved radiated energy efficiency and the increased power consumption for a given number of transceiver chains. The simulation and analytical results show that the proposed algorithm performs better than the reference algorithms by maximizing the overall energy efficiency of the system without much complexity.

https://www.mdpi.com/1996-1073/12/11/2227/pdf

On the Energy Efficiency of Millimeter Wave Massive MIMO Based on Hybrid Architecture

The key challenge faced by future wireless communications systems is to provide high-data-rate wireless access at high quality of service (QOS). Multiple-input multiple-output (MIMO) wireless technology seems to meet these demands by offering increased spectral efficiency through spatial multiplexing gain, and improved link reliability due to antenna diversity gain. OFDM may be combined with antenna arrays at the transmitter and receiver to increase bandwidth efficiency and robustness using multipath signal propagation, resulting in a MIMO-OFDM configuration. The forward error correction (FEC) along with powerful interleaving algorithms plays an important role in the improvement of the performance of the MIMO-OFDM systems. In this paper we have designed a simple MIMO OFDM system with convolutional coding with code rate 1/2 and analysed the performance of the system using different antenna configuration in AWGN channel. It was concluded higher antenna configuration give best performance.

Design and performance analysis of MIMO-OFDM system using different antenna configurations

MIMO is a technology that utilizes multiple antennas at transmitter/receiver to improve the throughput, capacity and coverage of wireless system. Massive MIMO where Base Station is equipped with orders of magnitude more antennas have shown over 10 times spectral efficiency increase over MIMO with simpler signal processing algorithms. Massive MIMO has benefits of enhanced capacity, spectral and energy efficiency and it can be built by using low cost and low power components. Despite its potential benefits, this paper also summarizes some challenges faced by massive MIMO such as antenna spatial correlation and mutual coupling as well as non-linear hardware impairments. These challenges encountered in massive MIMO uncover new problems that need further investigation.

Massive MIMO for Fifth Generation (5G): Opportunities and Challenges

Large-scale antenna arrays have been the current interest in the study of massive MIMO as a promising technology for 5G. Planar arrays have become the suitable antenna array configurations for massive MIMO since they provide directive beams. In this paper, planar array is proposed with square and rectangular arrangements based on 2 × 2 antenna elements as one subarray. Then, array factor (AF) for the planar array based on the subarray with up to 64 antenna elements is calculated to analyze the effects of inter element spacing on large antenna array characteristics. It is observed that large number of antenna elements contribute to large number of side lobes in the AF pattern and higher directivity at the expense of narrower HPBW. Inter element spacing less than 0.51 produces lower directivity and higher HPBW. Therefore, inter element spacing equal or larger than 0.51 is suitable to achieve higher directivity for large antenna array applications.

Effects of inter element spacing on large antenna array characteristics

Antenna array of large scale have been examined for different applications including 5G technology. To get better data rate or a reliable link substantial number of antenna arrays have been utilized to provide high multiplexing gains as well as array gains with high directivity. In this paper a simple but efficient implementation technique of using sub-arrays for the improvement of large-sized uniform arrays. By repeating a small sub-array multiple times large arrays can be designed. This implication of utilizing small array simplifies the design of a larger array which allows the designer to concentrate on the smaller sub-array before assembling larger arrays. So, by investigating the sub arrays the performance and radiation characteristics of large arrays can be anticipated. The array-factor for a planar sub-array of 2x2 (4 elements) is analyzed using Mat-lab software and then a large array is formed by pl acing the 2x2 sub-array indifferent configurations in a rectangular arrangements up to 8x8 planar array. A nd then the results are validated with CST (Computer simulation technology) simulation results .In this way the array-factors, directivities, HPBWs, and side lobes of the constructed large arrays are analyzed and associated with the small sub-array.

http://journal.portalgaruda.org/index.php/EEI/article/download/1846/1306

Designing large-scale antenna array using sub-array

Planar array antenna is seen as one of the innovative solutions of massive MIMO and 5G networks since they provide directive beams. In this paper, planar array antenna with square and rectangular arrangements based on 2 x 2 antenna elements as one subarray was proposed. Then, array factor for the the planar array antenna with up to 64 antenna elements was calculated to analyze the effects of inter-element spacing and number of elements on the antenna characteristics. Higher values of inter-element spacing contributed to higher number of side lobes, narrower main lobe, higher directivity and lower half power beamwidth (HPBW). Inter-element spacing equals to 0.5λ was found to be the most suitable value for planar array antenna design based on the analysis. Meanwhile, higher number of antenna elements increased the value of directivity of the planar array with narrower HPBW. Therefore, there is a tradeoff between directivity and HPBW in designing planar array antenna for massive MIMO application.

/pdf/effects-of-inter-element-spacing-and-number-of-elements-on-2uapkc9x6n.pdf

Effects of Inter-Element Spacing and Number of Elements on Planar Array Antenna Characteristics

Large-scale antenna arrays have been studied for a variety of applications including 5G technology. Large number of antenna arrays provide high multiplexing gains and array gains with high directivity for better performance in terms of data rate or link reliability. This paper implements a simple and efficient technique of using sub-arrays for the development of large uniform arrays. Large arrays can be formed by repeating a small sub-arrays throughout the rest of the large array. The use of sub-arrays simplifies the large array design by allowing the designer to concentrate on the smaller sub-array before constructing larger arrays. Thus, the performance and radiation characteristics of large arrays can be predicted through the investigation of sub-arrays. The array-factor for a planar subarray of 2x2 (4 elements) is analysed using Mat-lab software and then a large arrays are formed by placing the 2x2 sub-array in three different configurations i.e., in a rectangular, square and linear arrangements up to 16x16 planar array. Thus, the arrayfactors, directivities, HPBWs, and sidelobes of the constructed large arrays have been analysed and compared with the small sub-array.

/pdf/scalability-analysis-for-designing-large-scale-antenna-array-2k31gs73y4.pdf

Noor Hidayah M Adnan

Papers

Massive MIMO for Fifth Generation (5G): Opportunities and Challenges

Effects of inter element spacing on large antenna array characteristics

Designing large-scale antenna array using sub-array

Effects of Inter-Element Spacing and Number of Elements on Planar Array Antenna Characteristics

Scalability Analysis for Designing Large-Scale Antenna Array Using Sub-Array