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2022 ◽  
Vol 22 (2) ◽  
pp. 1-21
Lea Dujić Rodić ◽  
Tomislav Županović ◽  
Toni Perković ◽  
Petar Šolić ◽  
Joel J. P. C. Rodrigues

The Internet-of-Things vision of ubiquitous and pervasive computing gives rise to future smart irrigation systems comprising the physical and digital worlds. A smart irrigation ecosystem combined with Machine Learning can provide solutions that successfully solve the soil humidity sensing task in order to ensure optimal water usage. Existing solutions are based on data received from the power hungry/expensive sensors that are transmitting the sensed data over the wireless channel. Over time, the systems become difficult to maintain, especially in remote areas due to the battery replacement issues with a large number of devices. Therefore, a novel solution must provide an alternative, cost- and energy-effective device that has unique advantage over the existing solutions. This work explores the concept of a novel, low-power, LoRa-based, cost-effective system that achieves humidity sensing using Deep Learning techniques that can be employed to sense soil humidity with high accuracy simply by measuring the signal strength of the given underground beacon device.

Hayder M. Amer ◽  
Ethar Abduljabbar Hadi ◽  
Lamyaa Ghaleb Shihab ◽  
Hawraa H. Al Mohammed ◽  
Mohammed J. Khami

Technology such as vehicular ad hoc networks can be used to enhance the convenience and safety of passenger and drivers. The vehicular ad hoc networks safety applications suffer from performance degradation due to channel congestion in high-density situations. In order to improve vehicular ad hoc networks reliability, performance, and safety, wireless channel congestion should be examined. Features of vehicular networks such as high transmission frequency, fast topology change, high mobility, high disconnection make the congestion control is a challenging task. In this paper, a new congestion control approach is proposed based on the concept of hybrid power control and contention window to ensure a reliable and safe communications architecture within the internet of vehicles network. The proposed approach performance is investigated using an urban scenario. Simulation results show that the network performance has been enhanced by using the hybrid developed strategy in terms of received messages, delay time, messages loss, data collision and congestion ratio.

2022 ◽  
Vol 18 (1) ◽  
pp. 1-23
Mahabub Hasan Mahalat ◽  
Dipankar Karmakar ◽  
Anindan Mondal ◽  
Bibhash Sen

The deployment of wireless sensor networks (WSN) in an untended environment and the openness of the wireless channel bring various security threats to WSN. The resource limitations of the sensor nodes make the conventional security systems less attractive for WSN. Moreover, conventional cryptography alone cannot ensure the desired security against the physical attacks on sensor nodes. Physically unclonable function (PUF) is an emerging hardware security primitive that provides low-cost hardware security exploiting the unique inherent randomness of a device. In this article, we have proposed an authentication and key sharing scheme for the WSN integrating Pedersen’s verifiable secret sharing (Pedersen’s VSS) and Shamir’s secret sharing (Shamir’s SS) scheme with PUF which ensure the desired security with low overhead. The security analysis depicts the resilience of the proposed scheme against different active, passive and physical attacks. Also, the performance analysis shows that the proposed scheme possesses low computation, communication and storage overhead. The scheme only needs to store a polynomial number of PUF challenge-response pairs to the user node. The sink or senor nodes do not require storing any secret key. Finally, the comparison with the previous protocols establishes the dominance of the proposed scheme to use in WSN.

Bingxin Yao ◽  
Bin Wu ◽  
Siyun Wu ◽  
Yin Ji ◽  
Danggui Chen ◽  

In this paper, an offloading algorithm based on Markov Decision Process (MDP) is proposed to solve the multi-objective offloading decision problem in Mobile Edge Computing (MEC) system. The feature of the algorithm is that MDP is used to make offloading decision. The number of tasks in the task queue, the number of accessible edge clouds and Signal-Noise-Ratio (SNR) of the wireless channel are taken into account in the state space of the MDP model. The offloading delay and energy consumption are considered to define the value function of the MDP model, i.e. the objective function. To maximize the value function, Value Iteration Algorithm is used to obtain the optimal offloading policy. According to the policy, tasks of mobile terminals (MTs) are offloaded to the edge cloud or central cloud, or executed locally. The simulation results show that the proposed algorithm can effectively reduce the offloading delay and energy consumption.

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Shahzad Hassan ◽  
Noshaba Tariq ◽  
Rizwan Ali Naqvi ◽  
Ateeq Ur Rehman ◽  
Mohammed K. A. Kaabar

Wireless communication systems have evolved and offered more smart and advanced systems like ad hoc and sensor-based infrastructure fewer networks. These networks are evaluated with two fundamental parameters including data rate and spectral efficiency. To achieve a high data rate and robust wireless communication, the most significant task is channel equalization at the receiver side. The transmitted data symbols when passing through the wireless channel suffer from various types of impairments, such as fading, Doppler shifts, and Intersymbol Interference (ISI), and degraded the overall network performance. To mitigate channel-related impairments, many channel equalization algorithms have been proposed for communication systems. The channel equalization problem can also be solved as a classification problem by using Machine Learning (ML) methods. In this paper, channel equalization is performed by using ML techniques in terms of Bit Error Rate (BER) analysis and comparison. Radial Basis Functions (RBFs), Multilayer Perceptron (MLP), Support Vector Machines (SVM), Functional Link Artificial Neural Network (FLANN), Long-Short Term Memory (LSTM), and Polynomial-based Neural Networks (NNs) are adopted for channel equalization.

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 171
Mohammed J. Khafaji ◽  
Maciej Krasicki

A recently developed adaptive channel equalizer driven by a so-called Uni-Cycle Genetic Algorithm (UCGA) is examined in the paper. The authors consider different initialization strategies of the iterative process and compare UCGA against the reference Recursive Least Squares (RLS) algorithm in terms of Bit Error Rate (BER) vs. Signal to Noise Ratio (SNR) performance and convergence rate of an adaptive channel equalizer. The results display a reasonable performance gain of UCGA over RLS for most of wireless channel models studied in the paper. Additionally, UCGA is capable of boosting the equalizer convergence. Thus, it can be considered a promising candidate for the future adaptive wireless channel equalizer.

2021 ◽  
Vol 14 (1) ◽  
pp. 442
Victor Fernandes ◽  
Thiago F. A. Nogueira ◽  
H. Vincent Poor ◽  
Moisés V. Ribeiro

This work introduces statistical models for the energy harvested from the in-home hybrid power line-wireless channel in the frequency band from 0 to 100 MHz. Based on numerical analyses carried out over the data set obtained from a measurement campaign together with the use of the maximum likelihood value criterion and the adoption of five distinct power masks for power allocation, it is shown that the log-normal distribution yields the best model for the energies harvested from the free-of-noise received signal and from the additive noise in this setting. Additionally, the total harvested energy can be modeled as the sum of these two statistically independent random variables. Thus, it is shown that the energies harvested from this kind of hybrid channel is an easy-to-simulate phenomenon when carrying out research related to energy-efficient and self-sustainable networks.

R. R. Abenov ◽  
E. V. Rogozhnikov ◽  
Ya. V. Kryukov ◽  
D. A. Pokamestov ◽  
P. A. Abenova

Introduction. This paper investigates a transmission system based on FBMC/OQAM multiplexing. This system is characterized by a high spectral efficiency, thereby attracting interest as an alternative transmission method in future wireless mobile communication standards. However, a disadvantage of the system is the high complexity of signal processing. There are numerous publications that study the FBMC/OQAM system from a theoretical perspective. This paper presents an experimental study of a transmission system based on FBMC/OQAM.Aim. Verification of a transmission system based on FBMC/OQAM multiplexing in a wireless channel.Materials and methods. Computer simulation modeling in Matlab and experimental research using Keysight and Rohde & Schwarz certified measuring instruments.Results. A model of synthesis and signal processing was developed, and a frame structure was proposed. The processing included synchronization, since the study was carried out in a wireless double-dispersive channel. Time synchronization was provided by the method of time-domain correlation. A preamble consisting of two symbols was used for CFO compensation. Channel estimation in FBMC/OQAM was conducted by pilot symbols spread over the time-frequency domain, a method with an auxiliary pilot to compensate for intrinsic interference, as well as Zero Forcing and a linear interpolator. As a result, dependences of the bit error rate on the Eb/N0 in various channels were obtained. An error rate of 10−4 was achieved under the Eb/N0 equal to 13.4 dB, 15.3 dB and 20.9 dB in the first, second and third channel, respectively.Conclusion. A FBMC/OQAM-based transmission system with a linear equalizer can operate without a cyclic prefix in a multipath wireless channel, providing comparable noise immunity to OFDM-CP. Long frames should be used to obtain greater spectral efficiency, due to the presence of a transition zone at the beginning and end of the FBMC/OQAM frame.

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 59
Gavin Megson ◽  
Sabyasachi Gupta ◽  
Syed Muhammad Hashir ◽  
Ehsan Aryafar ◽  
Joseph Camp

Full-duplex (FD) communication in many-antenna base stations (BSs) is hampered by self-interference (SI). This is because a FD node’s transmitting signal generates significant interference to its own receiver. Recent works have shown that it is possible to reduce/eliminate this SI in fully digital many-antenna systems, e.g., through transmit beamforming by using some spatial degrees of freedom to reduce SI instead of increasing the beamforming gain. On a parallel front, hybrid beamforming has recently emerged as a radio architecture that uses multiple antennas per FR chain. This can significantly reduce the cost of the end device (e.g., BS) but may also reduce the capacity or SI reduction gains of a fully digital radio system. This is because a fully digital radio architecture can change both the amplitude and phase of the wireless signal and send different data streams from each antenna element. Our goal in this paper is to quantify the performance gap between these two radio architectures in terms of SI cancellation and system capacity, particularly in multi-user MIMO setups. To do so, we experimentally compare the performance of a state-of-the-art fully digital many antenna FD solution to a hybrid beamforming architecture and compare the corresponding performance metrics leveraging a fully programmable many-antenna testbed and collecting over-the-air wireless channel data. We show that SI cancellation through beam design on a hybrid beamforming radio architecture can achieve capacity within 16% of that of a fully digital architecture. The performance gap further shrinks with a higher number of quantization bits in the hybrid beamforming system.

2021 ◽  
Sulaiman Tariq ◽  
Hussain Al-Rizzo ◽  
Md Nazmul Hasan ◽  
Nijas Kunju ◽  
Said Abushamleh

Due to the rapid development of wireless communication applications, the study of Multiple Input Multiple Output (MIMO) communication systems has gained comprehensive research activities since it can significantly increase the channel capacity and link reliability without sacrificing bandwidth and/or transmitted power levels. Researchers tend to evaluate the performance of their MIMO antenna arrays using various channel modeling tools. These channel models are mainly categorized into either deterministic channels based on Ray Tracing (RT) tools or Stochastic Channel Models (SCM). In this chapter, we compare these two categories in terms of the MIMO channel capacity using a complete description of the antennas at the transmitting and receiving ends in terms of 3D polarimetric radiation patterns and scattering parameters. The performance is evaluated for 5G New Radio (NR) Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication (URLLC) services and Vehicle-to-Everything (V2X) systems using state-of-the-art commercial SCM and RT tools to provide information regarding the capabilities and limitations of each approach under different channel environments and the Quality of Experience (QoE) for high data rate and low latency content delivery in the 5G NR sub-6GHz mid-band Frequency Range-1 (FR1) N77/N78 bands.

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