Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding Systems

Khalid, Salman; Abbas, Waqas Bin; Kim, Hyung Seok; Niaz, Muhammad Tabish

doi:10.3390/s20185338

Cited by 11 publications

(4 citation statements)

References 45 publications

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“…Evolutionary algorithms for the joint computation of RF/digital precoders increase the SE of a partially connected hybrid precoding architecture. The paper titled Evolutionary-Algorithm-Based Capacity Maximization of 5G/B5G Hybrid Precoding Systems [ 17 ] considered the problem of spectrally efficient precoder design and presented an evolutionary-algorithm-based hybrid precoding strategy for partially connected antenna arrays in mmWave-massive MIMO systems. The proposed artificial bee-colony-based precoding scheme provided the highest achievable rates and outperformed benchmark evolutionary algorithms in terms of SE.…”

Section: Brief Review Of Technical Papersmentioning

confidence: 99%

Advanced Physical-Layer Technologies for Beyond 5G Wireless Communication Networks

Khalid

Ali

et al. 2021

Sensors

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Fifth-generation (5G) networks will not satisfy the requirements of the latency, bandwidth, and traffic density in 2030 and beyond, and next-generation wireless communication networks with revolutionary enabling technologies will be required. Beyond 5G (B5G)/sixth-generation (6G) networks will achieve superior performance by providing advanced functions such as ultralow latency, ultrahigh reliability, global coverage, massive connectivity, and better intelligence and security levels. Important aspects of B5G/6G networks require the modification and exploitation of promising physical-layer technologies. This Special Issue (SI) presents research efforts to identify and discuss the novel techniques, technical challenges, and promising solution methods of physical-layer technologies with a vision of potential involvement in the B5G/6G era. In particular, this SI presents innovations and concepts, including nonorthogonal multiple access, massive multiple-input multiple-output (MIMO), energy harvesting, hybrid satellite terrestrial relays, Internet of Things-based home automation, millimeter-wave bands, device-to-device communication, and artificial-intelligence or machine-learning techniques. Further, this SI covers the proposed solutions, including MIMO antenna design, modulation detection, interference management, hybrid precoding, and statistical beamforming along with their performance improvements in terms of performance metrics, including bit error rate, outage probability, ergodic sum rate, spectrum efficiency, and energy efficiency.

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Section: Brief Review Of Technical Papersmentioning

confidence: 99%

Advanced Physical-Layer Technologies for Beyond 5G Wireless Communication Networks

Khalid

Ali

et al. 2021

Sensors

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“…This research direction shows the influence of the patterns and parameters of antenna systems and the angular dispersion occurring in the real multipath propagation environment on the channel capacity determination. Recently, most of the research on capacity has been devoted to 5G technologies (e.g., [22][23][24][25][26]), networks, and systems [2,9,27,28]. In particular, the analysis of the signal propagation directions from the TX to the RX is crucial for systems based on beamforming and massive-MIMO technologies [25,26].…”

Section: Related Workmentioning

confidence: 99%

Radio Channel Capacity with Directivity Control of Antenna Beams in Multipath Propagation Environment

Ziółkowski

Kelner

Krygier

et al. 2021

Sensors

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The basic technology that will determine the expansion of the technical capabilities of fifth generation cellular systems is a massive multiple-input-multiple-output. Therefore, assessing the influence of the antenna beam orientations on the radio channel capacity is very significant. In this case, the effects of mismatching the antenna beam directions are crucial. In this paper, the methodology for evaluating changes in the received signal power level due to beam misalignment for the transmitting and receiving antenna systems is presented. The quantitative assessment of this issue is presented based on simulation studies carried out for an exemplary propagation scenario. For non-line-of-sight (NLOS) conditions, it is shown that the optimal selection of the transmitting and receiving beam directions may ensure an increase in the level of the received signal by several decibels in relation to the coaxial position of the beams. The developed methodology makes it possible to analyze changes in the radio channel capacity versus the signal-to-noise ratio and distance between the transmitter and receiver at optimal and coaxial orientations of antenna beams for various propagation scenarios, considering NLOS conditions. In the paper, the influence of the directional antenna use and their direction choices on the channel capacity versus SNR and the distance between the transmitter and receiver is shown.

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“…Another technique discussed in [16] involves an evolutionary algorithms based scheme known as particle swarm optimization (PSO) algorithm for a precoder design that achieves an EE as close to an optimum precoder. Compared to PSO, a performance improvement using artificial bee colony algorithm is shown in [17]. In another work, signal-to-leakage noise ratio (SLNR) has been used for the design of an analog precoder while the digital precoder is designed with the help of zero forcing (ZF) technique [18].…”

Section: Introductionmentioning

confidence: 99%

Heuristic Antenna Selection and Precoding for a Massive MIMO System

Abbas,

Khalid,

Ahmed

et al. 2024

IEEE Open J. Commun. Soc.

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Sixth Generation (6G) transceivers are envisioned to feature massively large antenna arrays compared to its predecessor. This will result in even higher spectral efficiency (SE) and multiplexing gains. However, immense concerns remain about the energy efficiency (EE) of such transceivers. This work focuses on partially connected hybrid architectures, with the primary aim of enhancing the EE of the system. To achieve this objective, the study proposes a combined approach of joint antenna selection and precoding, which holds the potential to further optimize the system's EE while maintaining a satisfactory SE performance levels. The proposed approach incorporates antenna selection based on a meta-heuristic cyclic binary particle swarm optimization algorithm along with successive interference cancellation-based precoding. The results indicate that the proposed solution, in terms of SE and EE, performs very close to the optimal exhaustive search algorithm. This study also investigates the trade-off between SE and EE in a low and high signal-to-noise ratio (SNR) regimes. The robustness of the proposed scheme is also demonstrated when the channel state information is imperfect. In conclusion, this work presents a lower complexity approach to enhance EE in 6G transceivers while maintaining SE performance and along with a reduction in power consumption.

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Evolutionary Algorithm Based Capacity Maximization of 5G/B5G Hybrid Pre-Coding Systems

Cited by 11 publications

References 45 publications

Advanced Physical-Layer Technologies for Beyond 5G Wireless Communication Networks

Advanced Physical-Layer Technologies for Beyond 5G Wireless Communication Networks

Radio Channel Capacity with Directivity Control of Antenna Beams in Multipath Propagation Environment

Heuristic Antenna Selection and Precoding for a Massive MIMO System

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