A Novel Efficient Initial Access Method for 5G Millimeter Wave Communications Using Genetic Algorithm

Souto, Victoria Dala Pegorara; Souza, Richard Demo; Uchôa-Filho, Bartolomeu F.; Li, Yonghui

doi:10.1109/tvt.2019.2935695

Cited by 24 publications

(9 citation statements)

References 38 publications

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“…The concept of GAs is based on the Theory of Evolution by natural selection, as proposed by Charles Darwin [ 39 ], in which individuals change over time and these changes help them to survive and to reproduce in order to generate descendants in the next generations. GAs are known to have simple implementation and to deliver good results in many optimization problems [ 23 , 40 ]. The terms typically used in GA come from biology, and for facilitating understanding, Table 1 lists the main terms used in this work and their meaning in the proposed optimization problem.…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Intelligent Reflecting Surfaces Beamforming Optimization with Statistical Channel Knowledge

Souto

Souza

Uchôa-Filho

et al. 2022

Sensors

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Intelligent Reflecting Surfaces (IRSs) are emerging as an effective technology capable of improving the spectral and energy efficiency of future wireless networks. The proposed scenario consists of a multi-antenna base station and a single-antenna user that is assisted by an IRS. The large number of reflecting elements at the IRS and its passive operation represent an important challenge in the acquisition of the instantaneous channel state information (I-CSI) of all links as it adds a very high overhead to the system and requires equipping the IRS with radio-frequency chains. To overcome this problem, a new approach is proposed in order to optimize beamforming at the BS and the phase shifts at the IRS without considering any knowledge of I-CSI but while only exploring the statistical channel state information (S-CSI). We aim at maximizing the user-achievable rate subject to a maximum transmit power constraint. To achieve this goal, we propose a new two-phase framework. In the first phase, both the beamforming at the BS and IRS are designed based only on S-CSI and, in the second phase, the previously designed beamforming pair is used as an initial solution, and beamforming at the BS and IRS is designed only by considering the feedback of the SNR at UE. Moreover, for each phase, we propose new methods based on Genetic Algorithms. Results show that the developed algorithms can approach beamforming with I-CSI but with significantly reduced channel estimation overhead.

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Section: Genetic Algorithmsmentioning

confidence: 99%

Intelligent Reflecting Surfaces Beamforming Optimization with Statistical Channel Knowledge

Souto

Souza

Uchôa-Filho

et al. 2022

Sensors

Self Cite

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“…These individuals are more likely to reproduce, thus producing more successors in the next generations. Because of the less operating costs, ease of implementation, and easy parallelization, GA has been implemented in numerous optimization problems [19]. Several approaches and terminologies from biology are applied as a theoretical base in GA.…”

Section: Literature Reviewmentioning

confidence: 99%

Multipath Routing Protocol Using Genetic Algorithm in Mobile Ad Hoc Networks

Bhardwaj

El-Ocla

2020

IEEE Access

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Mobile ad hoc network (MANET) is a cluster of wireless mobile gadgets that creates a temporary network without seeking support from any infrastructure or central management. Energy consumption should be considered as one of the foremost vital limitations in MANETs because the mobile nodes do not possess a constant power supply and its shortage will minimize the network's lifetime. MANETs get energy from the batteries which get exhausted very quickly because of issues like node mobility, computation power, frequent data retransmissions needed in wireless communication, etc. Secondly, there is a data packet loss caused by different reasons such as traffic congestion or random loss as a result of nodes mobility or noise. This data loss, in turn, would delay packets delivery degrading data transmission in real-time applications. This paper provides management for this combination of major problems in MANETs. We present a new fitness function (FFn) used in the Genetic Algorithm (GA) to obtain the optimized route from those routes offered by the Ad hoc On-demand Multipath Distance Vector (AOMDV) routing protocol. Accordingly, we propose a routing protocol titled as AOMDV with FFn (AOMDV-FFn). We also integrate the AOMDV mechanism with the genetic algorithm (AOMDV-GA). These protocols provide an optimization process to select the efficient routes that have the highest fitness values implementing the shortest route, maximum residual energy, and less data traffic even if a random loss of data packets happens. In this regard, we introduce a mechanism where the TCP Congestion Control Enhancement for Random Loss (TCP CERL) can be utilized in the FFn to optimize the efficient route. The performance of the proposed mechanisms is compared with other preferred protocols proposed in this area. INDEX TERMS congestion control, energy-efficient protocol, fitness function, genetic algorithm, mobile ad hoc network, multipath routing, shortest distance.

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“…Moreover, the work in 44 proposes the use of online machine learning algorithms for beam detection for vehicular communications at mmWave. The works in 33,42,54 use game-theoretic methods, whereas in 27,48 , the authors use genetic algorithms for initial beam discovery.…”

Section: Related Workmentioning

confidence: 99%

Energy and Latency of Beamforming Architectures for Initial Access in mmWave Wireless Networks

Barati

Dutta²,

Rangan³

et al. 2020

J Indian Inst Sci

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Future millimeter-wave systems, 5G cellular or WiFi, must rely on highly directional links to overcome severe pathloss in these frequency bands. Establishing such links requires the mutual discovery of the transmitter and the receiver, potentially leading to a large latency and high energy consumption. In this work, we show that both the discovery latency and energy consumption can be significantly reduced using fully digital front-ends. In fact, we establish that by reducing the resolution of the fully digital front-ends we can achieve lower energy consumption compared to both analog and high-resolution digital beamforming. Since beamforming through analog front-ends allows sampling in only one direction at a time, the mobile device is “on” for a longer time compared to a digital beamformer, which can get spatial samples from all directions in one shot. We show that the energy consumed by the analog front-end can be four to six times more than that of the digital front-ends, depending on the size of the employed antenna arrays. We recognize, however, that using fully digital beamforming post beam discovery, i.e., for data transmission, is not viable from a power consumption standpoint. To address this issue, we propose the use of digital beamformers with low-resolution analog to digital converters (4 bits). This reduction in resolution brings the power consumption to the same level as analog beamforming for data transmissions while benefiting from the spatial multiplexing capabilities of fully digital beamforming, thus reducing initial discovery latency and improving energy efficiency.

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A Novel Efficient Initial Access Method for 5G Millimeter Wave Communications Using Genetic Algorithm

Cited by 24 publications

References 38 publications

Intelligent Reflecting Surfaces Beamforming Optimization with Statistical Channel Knowledge

Intelligent Reflecting Surfaces Beamforming Optimization with Statistical Channel Knowledge

Multipath Routing Protocol Using Genetic Algorithm in Mobile Ad Hoc Networks

Energy and Latency of Beamforming Architectures for Initial Access in mmWave Wireless Networks

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