Antenna Selection and Power Allocation in Massive MIMO

Selvam, P.; Vishvaksenan, K. S.

doi:10.13164/re.2019.0340

Cited by 5 publications

(4 citation statements)

References 27 publications

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“…With MAE > 4, the imputed values are off by a larger unit than the other techniques. An offset of 10 dBm, 4 dBm, and 3 dBm in RSRP is equivalent to a 10 mW, 2.5 mW, and 1.99 mW in received signal power, respectively, which can be critical in radio resource allocation [53]. The mode imputation displays the worst performance and cannot be used for the task.…”

Section: Imputing the Data: Taskmentioning

confidence: 99%

Machine Learning-Based Imputation Approach with Dynamic Feature Extraction for Wireless RAN Performance Data Preprocessing

Dahj,

Ogudo

2023

Symmetry

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Machine learning (ML) in wireless mobile communication is becoming more and more customary, with application trends leaning toward performance improvement and network automation. The radio access network (RAN), critical for service access, frequently generates performance data that mobile network operators (MNOs) and researchers leverage for planning, self-optimization, and intelligent network operations. However, missing values in the RAN performance data, as in any valuable data, impact analysis. Poor handling of such missing data in the RAN can distort the relationships between different metrics, leading to inaccurate and unreliable conclusions and predictions. Therefore, there is a need for imputation methods that preserve the overall structure of the RAN data to an optimal level. In this study, we present an imputation approach for handling RAN performance missing data based on machine learning algorithms. The method customizes the feature-extraction mechanism by using dynamic correlation analysis. We apply the method to actual RAN performance indicator data to evaluate its performance. We finally compare and evaluate the proposed approach with statistical imputation techniques such as the mean, median, and mode. The results show that machine learning-based imputation, as approached in this experimental study, preserves some relationships between KPIs compared to non-ML techniques. Random Forest regressor gave the best performance in imputing the data.

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Section: Imputing the Data: Taskmentioning

confidence: 99%

Machine Learning-Based Imputation Approach with Dynamic Feature Extraction for Wireless RAN Performance Data Preprocessing

Dahj,

Ogudo

2023

Symmetry

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“…The bandwidth that can be generated is one of the things that can be studied in antenna design. The wider the bandwidth, the faster the data transmission, which is directly proportional to the throughput that can be generated [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

Scalable modular massive MIMO antenna of rectangular truncated corner patch antenna and circular slotted X patch antenna for 5G antenna communication

Salsabila,

Pudjiastuti,

Nur

et al. 2023

J.INFOTEL

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Massive MIMO Antenna Design results in a very large antenna size that hinders the design process. The arrangement of Massive MIMO Antennas which consists of many antenna elements is a challenge in the design process due to the limited capability of the simulation software and the complicated process. Thus, a scalability technique is used to predict the specification results produced by a Massive MIMO Antenna array with a certain configuration based on a simple MIMO Antenna array with a 2x2, 4x4, 8x8, 16x16 MIMO element configuration scheme, etc. exponential increments. This research will discuss the scaling process to predict the specifications of a Massive MIMO Antenna array. The designed MIMO antenna arrangement is based on the design of a rectangular antenna with a truncated corner and a circular antenna with an X slot for further design with various types of configurations that work at a frequency of 3.5 GHz.

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“…It satisfies to large data rates that require an effective and reliable digital transmission [2]. Multiple RF chains are required for multiple antennas with amplifiers, analog to digital converters, mixers, etc., but they are more expensive [3,4]. In MIMO system has two techniques, one kind of technique is spatial multiplexing and another kind of technique is Space Time Coding (STC).…”

Section: Introductionmentioning

confidence: 99%

Performance of Transmit Antenna Selection in Multiple Input Multiple Output-Orthogonal Space Time Block Code (MIMO-OSTBC) System Joint with Bose-Chaudhuri-Hocquenghem (BCH)-Turbo Code (TC) in Rayleigh Fading Channel

Deotale

2021

IJIE

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The Transmit antenna selection (TAS) technique is essential to increase the efficiency of spatial modulation (SM) systems. This TAS is an effective technique for reducing the Multiple Input Multiple Output (MIMO) systems, which can increase the computational difficulty and Bit error rate (BER) by various TAS algorithms. But these selection methods cannot provide code gain, so it is essential to join the external code in TAS to obtain code gain advantages in BER. In some existing work, the improved BER has been perceived by joining Forward Error Correction Code (FEC) and Space Time Block Code (STBC) for MIMO systems provided greater code gain. A multiple TAS-OSTBC technique with new integration of Bose–Chaudhuri–Hocquenghem (BCH)-Turbo code (TC) is proposed in this paper. The TAS-OSTBC system connects with the external BCH code in sequence of internal Turbo code. This combination can provide increasing code gain and the effective advantages of the TAS-OSTBC system. To perform the system analysis Rayleigh channel is utilized. In the case with multiple TAS-OSTBC systems, better performance can provide by this new combination of the BCH-Turbo compared to the conventional Turbo code for the Rayleigh fading.

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Antenna Selection and Power Allocation in Massive MIMO

Cited by 5 publications

References 27 publications

Machine Learning-Based Imputation Approach with Dynamic Feature Extraction for Wireless RAN Performance Data Preprocessing

Machine Learning-Based Imputation Approach with Dynamic Feature Extraction for Wireless RAN Performance Data Preprocessing

Scalable modular massive MIMO antenna of rectangular truncated corner patch antenna and circular slotted X patch antenna for 5G antenna communication

Performance of Transmit Antenna Selection in Multiple Input Multiple Output-Orthogonal Space Time Block Code (MIMO-OSTBC) System Joint with Bose-Chaudhuri-Hocquenghem (BCH)-Turbo Code (TC) in Rayleigh Fading Channel

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