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Journal articles on the topic 'Picocell'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 June 2025

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1

Li, Yuan, Li Zhang, Hua Chen, and Mugen Peng. "Interference Coordination in Multiple Antenna Based LTE-Advanced Heterogeneous Systems." International Journal of Antennas and Propagation 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/167368.

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With picocells deployed in the coverage of a macrocell in heterogeneous networks (HetNets), the macrocell evolved NodeB (MeNB) may receive interference signals from the picocell users, which results in more severe co-channel interference (CCI) problem in the uplink. In this paper, the spatial uplink interference coordination is investigated in multiple antenna systems, according to which the receiver coding matrix is generated by MeNB to mitigate the CCI from picocell users. Two interference coordination (IC) schemes are proposed based on whether the receiver coding matrix is full rank or not, named as full coding (IC-FC) and part coding (IC-PC), respectively. The application of the proposed schemes is discussed in single picocell and multiple picocell scenarios. The CCI can be totally canceled in single picocell scenario, and an algorithm is developed in multiple picocell networks to mitigate the most severely interfering picocell. Link level and system level simulations are applied, and it is shown that significant performance gain is achieved by our proposed schemes over traditional IC receivers.

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2

Yasaka, Takumi, Kentaro Yoda, and Hiroyuki Otsuka. "Optimization of Pico-eNB Tx Power and the Effects of Picocell Range Expansion in Multiband HetNet." Journal of Sensor and Actuator Networks 11, no. 2 (2022): 27. http://dx.doi.org/10.3390/jsan11020027.

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The use of heterogeneous networks (HetNets) that combine macrocells and picocells in the same coverage is effective in increasing system capacity and improving user throughput. The use of high carrier frequency bands is also expected to help achieving higher data rates because it promises vast amounts of signal bandwidth. Therefore, multiband HetNets with picocells operating at high carrier frequency bands have attracted significant attention with the aim of increasing system capacity and achieving a high user throughput in fifth-generation mobile systems and beyond. In HetNet deployments, a picocell range expansion (CRE) technique that virtually expands the picocell coverage is well known to allow more user equipment (UE) to access the picocell providing a fixed cell selection offset (CSO) for all UE. Thus far, there has not been sufficient research on optimizing the transmission (Tx) power of pico-evolved node Bs (eNBs) operating at high carrier frequency bands in multiband HetNets. In addition, the effects of CRE in multiband HetNets have not been clarified. In this paper, we first investigated the optimal Tx power of pico-eNB in a multiband HetNet combining macrocells operating at 2 GHz and picocells operating at 4.5 GHz band with a wider signal bandwidth using system-level computer simulations. Then, from the user throughput perspective, we investigated the effects of CRE providing a positive CSO for UE using two pico-eNB Tx powers close to the optimal value. Using these results, we discussed how to choose the pico-eNB Tx power when CRE was activated and validated the design method for a multiband HetNet.

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3

Fall, Macoumba, Mohammed Fattah, Mohammed Mahfoudi, et al. "Optimizing Energy Consumption in 5G HetNets: A Coordinated Approach for Multi-Level Picocell Sleep Mode with Q-Learning." Data and Metadata 3 (May 20, 2024): 333. http://dx.doi.org/10.56294/dm2024333.

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Cell standby, particularly picocell sleep mode (SM), is a prominent strategy for reducing energy consumption in 5G networks. The emergence of multi-state sleep states necessitates new optimization approaches. This paper proposes a novel energy optimization strategy for 5G heterogeneous networks (HetNets) that leverages macrocell-picocell coordination and machine learning. The proposed strategy focuses on managing the four available picocell sleep states. The picocell manages the first three states using the Q-learning algorithm, an efficient reinforcement learning technique. The associated macrocell based on picocell energy efficiency controls the final, deeper sleep state. This hierarchical approach leverages localized and network-wide control strengths for optimal energy savings. By capitalizing on macrocell-picocell coordination and machine learning, this work presents a promising solution for achieving significant energy reduction in 5G HetNets while maintaining network performance.

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4

Fujisawa, Kento, Fumiya Kemmochi, and Hiroyuki Otsuka. "Personal Picocell Scheme Using Adaptive Control CRE in Heterogeneous Mobile Networks." Journal of Sensor and Actuator Networks 9, no. 4 (2020): 48. http://dx.doi.org/10.3390/jsan9040048.

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Heterogeneous networks (HetNets), which are combined with a macrocell and picocell in the same coverage, are expected to further increase the system capacity in fifth-generation mobile systems and beyond. In HetNets, the cell range expansion (CRE) technique plays an important role and can allow more user equipment (UE) to access the picocell, i.e., virtually expand the picocell coverage. However, conventional CRE techniques that provide a fixed cell selection offset (CSO) for all UE may worsen user throughput if UE is forced to connect to the picocell because the received signal-to-interference plus noise ratio of the UE becomes lower. Therefore, we propose a personal picocell scheme using an adaptive control CRE technique to improve user throughput in which different CSOs are assigned to UE to form each optimal picocell for each UE. In this paper, we first describe the aspects and algorithm of the proposed scheme. Then, we show the user throughput for adaptive control CRE in comparison with conventional CRE by using system-level computer simulations for the two types of HetNets, i.e., single-band and multi-band HetNets. In the simulations, we first clarify the optimal parameters of the adaptive control CRE. We then show the average and 5-percentile user throughput of the optimized adaptive control CRE in comparison with that of conventional CRE. From these results, we confirmed that the personal picocell scheme using the adaptive control CRE can improve the 5-percentile user throughput while maintaining the average user throughput compared with that of conventional CRE.

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5

Hadi, Supriadi, and Putri Hasanah. "Range expansion method on heterogeneous network to increase picocell coverage." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 5 (2020): 2341~2351. https://doi.org/10.12928/TELKOMNIKA.v18i5.14640.

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In this study, picocell planning was carried out on heterogeneous networks by applying the range expansion method. The case study was conducted in Coblong Subdistrict-Bandung on the 1800 MHz frequency. Heterogeneous network (HetNet) is a system that combines microcell networks and small cell networks (picocell and femtocell). The application of the range expansion method in picocell was aimed to broaden the scope of picocell. For the simulation, Atoll 3.3.0 software with observational parameters was implemented, including RSRP, SINR, throughput, and user connected. The planning results showed that the application of expansion method increased the coverage and quality of network, where the RSRP value ≥ -90 dBm was 97.72%, SINR ≥ 5 dB was 70.99%, uplink throughput was 17.80 Mbps, downlink throughput was 21.37 Mbps, and user connected was 99.2%.

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6

Andrita, Andrita Ceriana Eska, and Wahyu Muldayani. "HetNet Micro dan Pico Cell untuk AMC UE 10 GHz menggunakan SKE pada Lingkungan Bergedung." J-Innovation 12, no. 1 (2023): 1–6. http://dx.doi.org/10.55600/jipa.v12i1.166.

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User Equipment (UE) bergerak pada lintasan yang berada diantara gedung-gedung. UE tersebut menggunakan frekuensi 10 GHz. Metode Single Knife Edge (SKE) digunakan untuk mekanisme difraksi. Lintasan UE melewati HetNet (Heterogeneous Networks) yang terdiri dari microcell dan picocell. Propagasi UE kondisi uplink, dan kanal AWGN. AMC (Adaptive Modulation and Coding) yang digunakan memanfaatkan MCS (Modulation and Code Scheme) yang terdiri dari QPSK, 16QAM, dan 64QAM. Persentase cakupan yang menggunakan selection combining HetNet sebesar 95,52%, Node Base microcell 88,05%, dan Node Base picocell 56,71%. Persentase penggunaan selection combining dengan modulasi 64 QAM didapatkan 70,11%.

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7

Regmi, Hem, and Sanjib Sur. "Towards Deep Learning Augmented Robust D-Band Millimeter-Wave Picocell Deployment." ACM SIGMETRICS Performance Evaluation Review 50, no. 4 (2023): 62–64. http://dx.doi.org/10.1145/3595244.3595266.

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D-band millimeter-wave, a key wireless technology for beyond 5G networks, promises extremely high data rate, ultra-low latency, and enables new Internet of Things applications. However, massive signal attenuation, complex response to building structures, and frequent non-availability of the Line-Of-Sight path make D-band picocell deployment challenging. To address this challenge, we propose a deep learning-based tool, that allows a network deployer to quickly scan the environment from a few random locations and predict Signal Reflection Profiles everywhere, which is essential to determine the optimal locations for picocell deployment.

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8

Kumar, Suman, Sheetal Kalyani, and K. Giridhar. "Spectrum Allocation for ICIC-Based Picocell." IEEE Transactions on Vehicular Technology 64, no. 8 (2015): 3494–504. http://dx.doi.org/10.1109/tvt.2014.2360454.

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9

Yu, Xiang, Li Zhang, Wen Qing Wang, and Rong Wang. "A Handover Process Analysis Method in LTE-A Heterogeneous Network." Applied Mechanics and Materials 556-562 (May 2014): 5843–47. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.5843.

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10

Regmi, Hem, and Sanjib Sur. "Argus." ACM SIGMETRICS Performance Evaluation Review 50, no. 1 (2022): 29–30. http://dx.doi.org/10.1145/3547353.3522642.

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We propose Argus, a system to enable millimeter-wave (mmWave) deployers to quickly complete site-surveys without sacrificing the accuracy and effectiveness of thorough network deployment surveys. Argus first models the mmWave reflection profile of an environment, considering dominant reflectors, and then uses this model to find locations that maximize the usability of the reflectors. The key component in Argus is an effective deep learning model that can map the visual data to the mmWave signal reflections of an environment and can accurately predict mmWave signal profile at any unobserved locations. It allows Argus to find the best picocell locations to provide maximum coverage and also lets users self-localize accurately anywhere in the environment. Furthermore, Argus allows mmWave picocells to predict device's orientation accurately and enables object tagging and retrieval for VR/AR applications. We implement and validate Argus on two different buildings consisting of multiple different indoor environments. However, the generalization capability of Argus can easily update the model for unseen environments; so, Argus can be deployed to any indoor environment with little or no model fine-tuning.

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11

Regmi, Hem, and Sanjib Sur. "Argus." Proceedings of the ACM on Measurement and Analysis of Computing Systems 6, no. 1 (2022): 1–26. http://dx.doi.org/10.1145/3508022.

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We propose Argus, a system to enable millimeter-wave (mmWave) deployers to quickly complete site-surveys without sacrificing the accuracy and effectiveness of thorough network deployment surveys. Argus first models the mmWave reflection profile of an environment, considering dominant reflectors, and then use this model to find locations that maximize the usability of the reflectors. The key component in Argus is an efficient machine learning model that can map the visual data to the mmWave signal reflections of an environment and can accurately predict mmWave signal profile at any unobserved locations. It allows Argus to find the best picocell locations to provide maximum coverage and also lets users self-localize accurately anywhere in the environment. Furthermore, Argus allows mmWave picocells to predict device's orientation accurately and enables object tagging and retrieval for VR/AR applications. Currently, we implement and test Argus on two different buildings consisting of multiple different indoor environments. However, the generalization capability of Argus can easily update the model for unseen environments, and thus, Argus can be deployed to any indoor environment with little or no model fine-tuning.

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12

Xue, Wenqian, Hengzhi Zhang, Yong Li, Dong Liang, and Mugen Peng. "Cell Outage Detection and Compensation in Two-Tier Heterogeneous Networks." International Journal of Antennas and Propagation 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/624858.

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Heterogeneous networks (HetNets) can increase network capacity through complementing the macro-base-station with low-power nodes, in response to the ongoing exponential growth in data traffic demand. While, unprecedented challenges exist in the planning, optimization, and maintenance in HetNets, especially activities such as cell outage detection and mitigation are labor-intensive and costly. One potential solution to address these issues is to introduce the extensively attracted self-organizing network (SON). This paper is mainly devoted to cell outage detection and compensation methods in two-tier HetNets where macrocell and picocells are coexisted. AK-nearest neighbor (KNN) classification algorithm is employed to detect the cell outage automatically. Consider the breakdown picocell can reload its degraded service to the overlapped macrocell via vertical handover; only the breakdown macrocell executes the performance compensation. Power adjustment on each resource block is carried out via Lagrange optimizing algorithm to compensate the breakdown cell. Through intensive numerical experiments, with the help of our proposal, the outage cells can be successfully detected and performance gain for the outage macrocell can reach 91.4% withα=1/3.

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13

Chia, S. T. S., and W. Johnston. "Handover performance from microcell to indoor picocell." Electronics Letters 28, no. 3 (1992): 315. http://dx.doi.org/10.1049/el:19920195.

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14

Yang, Jie, Ziyu Pan, Hengfei Xu, and Han Hu. "Joint Optimization of Pico-Base-Station Density and Transmit Power for an Energy-Efficient Heterogeneous Cellular Network." Future Internet 11, no. 10 (2019): 208. http://dx.doi.org/10.3390/fi11100208.

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Heterogeneous cellular networks (HCNs) have emerged as the primary solution for explosive data traffic. However, an increase in the number of base stations (BSs) inevitably leads to an increase in energy consumption. Energy efficiency (EE) has become a focal point in HCNs. In this paper, we apply tools from stochastic geometry to investigate and optimize the energy efficiency (EE) for a two-tier HCN. The average achievable transmission rate and the total power consumption of all the BSs in a two-tier HCN is derived, and then the EE is formulated. In order to maximize EE, a one-dimensional optimization algorithm is used to optimize picocell BS density and transmit power. Based on this, an alternating optimization method aimed at maximizing EE is proposed to jointly optimize transmit power and density of picocell BSs. Simulation results validate the accuracy of the theoretical analysis and demonstrate that the proposed joint optimization method can obviously improve EE.

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15

Lou, Yi Feng, Wei Guo, and Wen Hui Xiong. "Energy Efficiency of Cell Range Extension of Picocell." Applied Mechanics and Materials 340 (July 2013): 507–11. http://dx.doi.org/10.4028/www.scientific.net/amm.340.507.

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Energy efficiency is an important issue in the wireless communication system as the increasing number of wireless network users and the emerging data usage. Heterogeneous network (HetNet) is a possible way to reduce the energy consumption since the distance between user equipment (UE) and the base station is shortened in HetNet, which sharply reduce the pathloss between the transmitter and receiver. This paper investigates the energy efficiency of Pico-Macro system in terms of Joule per bit. A effects of using Cell Range Extension (CRE) of Picocell based on energy efficiency is investigated and verified through the simulation results.

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16

Gedel, Ibrahim Alhassan, and Nnamdi I. Nwulu. "Low Latency 5G Distributed Wireless Network Architecture: A Techno-Economic Comparison." Inventions 6, no. 1 (2021): 11. http://dx.doi.org/10.3390/inventions6010011.

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The most profound requirements of fifth-generation (5G) technology implementations are the architecture design and the radio base station technology to capably run applications such as device-to-device, machine-to machine and internet of things at a reduced latency. Owing to these requirements, the implementation of 5G technology is very expensive to mobile network operators (MNO). In this study we modified the existing 4G network to form a distributed wireless network architecture (DWNA); the picocell and distributed antenna system were modified to support the enabling technology of 5G technology were a multi-edge computer (MEC), software-defined networking (SDN), massive multiple input multiple output (MIMO), ultra-dense network (UDN), Network Functions Virtualization (NFV) and device-to-device (D2D) communication at a reduced cost of ownership, improved coverage and capacity. We present a mathematical model for operational expenditure, capital expenditure and total cost of ownership (TCO) for the DWNA. A mathematical model for DWNA capacity and throughput was presented. Result shows that it is very economical for MNO to rent the space of the tower infrastructure from tower companies. The sensitivity analysis also shows a significant reduction in TCO for both the modified picocell and modified distributed antenna systems.

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17

Wake, D., D. Johansson, and D. G. Moodie. "Passive picocell: a new concept in wireless network infrastructure." Electronics Letters 33, no. 5 (1997): 404. http://dx.doi.org/10.1049/el:19970277.

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18

Park, Roy C., Hoill Jung, Kyungyong Chung, and Kun-Ho Yoon. "Picocell based telemedicine health service for human UX/UI." Multimedia Tools and Applications 74, no. 7 (2014): 2519–34. http://dx.doi.org/10.1007/s11042-014-1964-8.

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19

Kozoriz, D. A. "A SELF-ORGANIZING NETWORK WITH AN INFINITE OF NODES WITH A LIMITED NUMBER OF CHANNELS IN THE NODES AND A LIMITED QUEUE." RADIO COMMUNICATION TECHNOLOGY, no. 47 (November 23, 2020): 23–31. http://dx.doi.org/10.33286/2075-8693-2020-47-23-31.

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Self-organizing dynamic networks (SDN) or Ad-hoc networks are widely used in emergency communications systems and combat operations. Based on technology Wi-Fi, Bluetooth SDN are formed in the picocell. However, the analysis of the functioning of such networks is very difficult due to the randomness of their topol-ogy. In this work, we study networks using the previously proposed method of analysis based on the theory of Queuing.

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20

Callaghan, Peter, and John C. Batchelor. "Multiband Low-Profile Antenna for Remote Antenna Unit Picocell Applications." IEEE Transactions on Antennas and Propagation 56, no. 8 (2008): 2475–80. http://dx.doi.org/10.1109/tap.2008.927558.

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21

Supriadi, Hadi, and Hasanah Putri. "Range expansion method on heterogeneous network to increase picocell coverage." TELKOMNIKA (Telecommunication Computing Electronics and Control) 18, no. 5 (2020): 2341. http://dx.doi.org/10.12928/telkomnika.v18i5.14640.

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22

Sulonen, K., P. Suvikunnas, L. Vuokko, J. Kivinen, and P. Vainikainen. "Comparison of MIMO antenna configurations in picocell and microcell environments." IEEE Journal on Selected Areas in Communications 21, no. 5 (2003): 703–12. http://dx.doi.org/10.1109/jsac.2003.810297.

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23

Adityawarman, Fajar, Arfianto Fahmi, and Uke Kurniawan Usman. "ANALISIS PERENCANAAN JARINGAN LTE PICOCELL DI STADION UTAMA GELORA BUNG KARNO." TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika 3, no. 2 (2019): 48. http://dx.doi.org/10.25124/tektrika.v3i2.2223.

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Stadion Utama Gelora Bung Karno (SUGBK) adalah sebuah stadion serbaguna yang berstandar internasional dan sering dijadikan sebagai tempat untuk pertandingan olahraga nasional maupun internasional. Dengan kapasitas penonton yang banyak dan struktur bangunan yang menghalangi propagasi sinyal dari site outdoor menyebabkan kualitas sinyal sangat buruk sehingga perlu adanya perencanaan jaringan dari sisi kapasitas dan juga cakupan di dalam bangunan agar pelanggan tetap mendapatkan layanan yang baik dari kemampuan teknologi yang ada saat ini. Pada hasil perencanaan didapatkan nilai Reference Signal Received Power (RSRP) untuk keseluruhan area pada skenario 1 yaitu sebesar -74,10 dBm dan skenario 2 yaitu sebesar -74,08 dBm. Pada hasil perencanaan didapatkan nilai Signal to Interference Ratio (SIR) untuk keseluruhan area pada skenario 1 yaitu sebesar 19,04 dB dan skenario 2 yaitu sebesar 21,49 dB. Berdasarkan Key Performance Indicator (KPI) operator acuan yaitu untuk parameter RSRP harus > -90 dBm (90% area) dan parameter SIR harus > 0 dB (90% area) maka hasil prediksi disimulasi nilai RSRP & SIR skenario 1 dan 2 mencapai target KPI.

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24

Yifan Yu and Daqing Gu. "The Cost Efficient Location Management in the LTE Picocell/Macrocell Network." IEEE Communications Letters 17, no. 5 (2013): 904–7. http://dx.doi.org/10.1109/lcomm.2013.040213.130048.

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25

Jeong, Heejun, and Dong-Soo Shin. "Integrated Electroabsorption Modulator/Heterojunction Phototransistor for Passive-Picocell Radio-Over-Fiber Applications." Journal of the Korean Physical Society 54, no. 2 (2009): 774–79. http://dx.doi.org/10.3938/jkps.54.774.

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26

SHIMODAIRA, Hidekazu, Gia Khanh TRAN, Kei SAKAGUCHI, et al. "Optimization of Picocell Locations and Its Parameters in Heterogeneous Networks with Hotspots." IEICE Transactions on Communications E96.B, no. 6 (2013): 1338–47. http://dx.doi.org/10.1587/transcom.e96.b.1338.

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27

Cooper, T. G., S. M. Mann, M. Khalid, and R. P. Blackwell. "Public exposure to radio waves near GSM microcell and picocell base stations." Journal of Radiological Protection 26, no. 2 (2006): 199–211. http://dx.doi.org/10.1088/0952-4746/26/2/005.

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28

Tang, Hao, Jinlin Peng, Peilin Hong, and Kaiping Xue. "Offloading Performance of Range Expansion in Picocell Networks: A Stochastic Geometry Analysis." IEEE Wireless Communications Letters 2, no. 5 (2013): 511–14. http://dx.doi.org/10.1109/wcl.2013.061913.130346.

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29

Ndzi, David Lorater, Kenneth Stuart, Somboon Toautachone, Branislav Vuksanovic, and David A. Sanders. "WIDEBAND SOUNDER FOR DYNAMIC AND STATIC WIRELESS CHANNEL CHARACTERISATION: URBAN PICOCELL CHANNEL MODEL." Progress In Electromagnetics Research 113 (2011): 285–312. http://dx.doi.org/10.2528/pier10122905.

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30

Kavitha, Veeraruna, Sreenath Ramanath, and Eitan Altman. "Spatial queueing for analysis, design and dimensioning of Picocell networks with mobile users." Performance Evaluation 68, no. 8 (2011): 710–27. http://dx.doi.org/10.1016/j.peva.2011.03.002.

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31

Moon, Sangmi, Bora Kim, Saransh Malik, et al. "Cell Selection and Resource Allocation for Interference Management in a Macro-Picocell Heterogeneous Network." Wireless Personal Communications 83, no. 3 (2015): 1887–901. http://dx.doi.org/10.1007/s11277-015-2489-9.

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32

Perez, Jesus R., Rafael P. Torres, Marta Domingo, Luis Valle, and Jose Basterrechea. "Analysis of Massive MIMO Performance in an Indoor Picocell With High Number of Users." IEEE Access 8 (2020): 107025–34. http://dx.doi.org/10.1109/access.2020.3000602.

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33

Kassim, Abduljalal Yusha'u, Vitalice Kalecha Oduol, and Aliyu Danjuma Usman. "Design and performance evaluation of a 350 m free space optical communications link for pico-macrocell backhauling." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 3 (2024): 2725. http://dx.doi.org/10.11591/ijece.v14i3.pp2725-2736.

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Fibreless optics or free space optical communications (FSOC) has been at the forefront of many academic research in telecommunications due to its numerous benefits of large spectrum, high-speed data transmission, security, low transmit power, unlicensed spectrum and non-interfering links. Among the technical challenges of dense deployment of small cells in heterogeneous networks (HetNet) is a flexible and cost-effective backhaul link. This paper proposes, designs, simulates and evaluates the performance of a 350 m FSOC link under different atmospheric impairments for picocell to macrocell backhauling applications. The performance of the FSOC link is assessed by evaluating bit error rate (BER), eye diagram and quality factor (Q-factor). Results obtained recommend the FSOC link deployment for pico-macrocell backhauling under the weather conditions of clear sky with/without turbulence, heavy rain, heavy haze, heavy fog and wet snow.

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34

Lethien, Christophe, David Wake, Bernard Verbeke, et al. "Energy-Autonomous Picocell Remote Antenna Unit for Radio-Over-Fiber System Using the Multiservices Concept." IEEE Photonics Technology Letters 24, no. 8 (2012): 649–51. http://dx.doi.org/10.1109/lpt.2012.2185224.

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35

Yang, Jie, Han Hu, and Ziyu Pan. "Optimal Picocell Base Station Density for Energy-efficient Heterogeneous Cellular Network Under Received Power Constraint." International Journal of Communication Networks and Distributed Systems 25, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijcnds.2020.10021764.

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Yang, Jie, Ziyu Pan, and Han Hu. "Optimal picocell base station density for energy-efficient heterogeneous cellular network under received power constraint." International Journal of Communication Networks and Distributed Systems 25, no. 1 (2020): 43. http://dx.doi.org/10.1504/ijcnds.2020.108149.

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37

Lebedev, Alexander, Xiaodan Pang, J. J. Vegas Olmos, et al. "Feasibility Study and Experimental Verification of Simplified Fiber-Supported 60-GHz Picocell Mobile Backhaul Links." IEEE Photonics Journal 5, no. 4 (2013): 7200913. http://dx.doi.org/10.1109/jphot.2013.2277011.

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38

Abduljalal, Yusha'u Kassim, Kalecha Oduol Vitalice, and Danjuma Usman Aliyu. "Design and performance evaluation of a 350 m free space optical communications link for pico-macrocell backhauling." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 3 (2024): 2725–36. https://doi.org/10.11591/ijece.v14i3.pp2725-2736.

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Fibreless optics or free space optical communications (FSOC) has been at the forefront of many academic research in telecommunications due to its numerous benefits of large spectrum, high-speed data transmission, security, low transmit power, unlicensed spectrum and non-interfering links. Among the technical challenges of dense deployment of small cells in heterogeneous networks (HetNet) is a flexible and cost-effective backhaul link. This paper proposes, designs, simulates and evaluates the performance of a 350 m FSOC link under different atmospheric impairments for picocell to macrocell backhauling applications. The performance of the FSOC link isassessed by evaluating bit error rate (BER), eye diagram and quality factor (Q-factor). Results obtained recommend the FSOC link deployment for picomacrocell backhauling under the weather conditions of clear sky with/without turbulence, heavy rain, heavy haze, heavy fog and wet snow.

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Sekulović, Nikola, Miloš Stojanović, Aleksandra Panajotović, and Miloš Banđur. "A comparative performance analysis of different machine learning techniques for SNR prediction in microcell and picocell wireless environment." International Journal of Reasoning-based Intelligent Systems 13, no. 4 (2021): 212. http://dx.doi.org/10.1504/ijris.2021.118645.

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Banđur, Miloš, Aleksandra Panajotović, Miloš Stojanović, and Nikola Sekulović. "A comparative performance analysis of different machine learning techniques for SNR prediction in microcell and picocell wireless environment." International Journal of Reasoning-based Intelligent Systems 13, no. 4 (2021): 212. http://dx.doi.org/10.1504/ijris.2021.10041240.

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Shin, D. S., W. R. Kim, S. K. Woo, and J. I. Shim. "Low-Detuning Operation of Electroabsorption Modulator as a Zero-Bias Optical Transceiver for Picocell Radio-Over-Fiber Applications." IEEE Photonics Technology Letters 20, no. 11 (2008): 951–53. http://dx.doi.org/10.1109/lpt.2008.922916.

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Bai, Wenle, Yu Xiao, Danping Hu, and Yongmei Zhang. "Application Research of Multi-Mode Relay in Future Heterogeneous Networks." Applied Sciences 9, no. 18 (2019): 3934. http://dx.doi.org/10.3390/app9183934.

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The fast increase of users in existing mobile networks requires more base stations (BSs) to bear more communication traffic. Future heterogeneous network is considered to be a promising candidate architecture to meet the demands of wireless networks under scarcity of radio frequency (RF) resources. In this paper, we present a multi-mode relay (MMR) model based on two-way relay technology, which is applied to heterogeneous hierarchical wireless networks (HHWN), and set up a system model of HHWN with 3 tiers, 2 users between the macrocell, and the picocell as the multi-mode relay (MMR). Specifically, we consider the new system with unequal relay emission power situation, which is usually researched in the traditional literature with equal relay emission powers. Based on this idea, we define the two-way SINR ratio, derive the mathematical formulas of outage error probability with channel estimation errors, and verify theoretical expressions by data simulations. For further comparison, several experiments are implemented to illuminate the effect on outage probability among different levels of relay emission power, noise power, and signal power. Furthermore, several conclusions are obtained, which have some meanings for implementing MMR in future heterogeneous networks.

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Catedra, M. F., J. Perez, F. Saez de Adana, and O. Gutierrez. "Efficient ray-tracing techniques for three-dimensional analyses of propagation in mobile communications: application to picocell and microcell scenarios." IEEE Antennas and Propagation Magazine 40, no. 2 (1998): 15–28. http://dx.doi.org/10.1109/74.683539.

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Afolabi, Akindele Segun, Shehu Ahmed, and Olubunmi Adewale Akinola. "A Reinforcement Learning Approach for Interference Management in Heterogeneous Wireless Networks." International Journal of Interactive Mobile Technologies (iJIM) 15, no. 12 (2021): 65. http://dx.doi.org/10.3991/ijim.v15i12.20751.

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<span lang="EN-US">Due to the increased demand for scarce wireless bandwidth, it has become insufficient to serve the network user equipment using macrocell base stations only. Network densification through the addition of low power nodes (picocell) to conventional high power nodes addresses the bandwidth dearth issue, but unfortunately introduces unwanted interference into the network which causes a reduction in throughput. This paper developed a reinforcement learning model that assisted in coordinating interference in a heterogeneous network comprising macro-cell and pico-cell base stations. The learning mechanism was derived based on Q-learning, which consisted of agent, state, action, and reward. The base station was modeled as the agent, while the state represented the condition of the user equipment in terms of Signal to Interference Plus Noise Ratio. The action was represented by the transmission power level and the reward was given in terms of throughput. Simulation results showed that the proposed Q-learning scheme improved the performances of average user equipment throughput in the network. In particular, </span><span lang="EN-US">multi-agent systems with a normal learning rate increased the throughput of associated user equipment by a whooping 212.5% compared to a macrocell-only scheme.</span>

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Gadam, M. A., Maryam Abdulazeez Ahmed, Chee Kyun Ng, Nor Kamariah Nordin, Aduwati Sali, and Fazirulhisyam Hashim. "Review of Adaptive Cell Selection Techniques in LTE-Advanced Heterogeneous Networks." Journal of Computer Networks and Communications 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/7394136.

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Poor cell selection is the main challenge in Picocell (PeNB) deployment in Long Term Evolution- (LTE-) Advanced heterogeneous networks (HetNets) because it results in load imbalance and intercell interference. A selection technique based on cell range extension (CRE) has been proposed for LTE-Advanced HetNets to extend the coverage of PeNBs for load balancing. However, poor CRE bias setting in cell selection inhibits the attainment of desired cell splitting gains. By contrast, a cell selection technique based on adaptive bias is a more effective solution to traffic load balancing in terms of increasing data rate compared with static bias-based approaches. This paper reviews the use of adaptive cell selection in LTE-Advanced HetNets by highlighting the importance of cell load estimation. The general performances of different techniques for adaptive CRE-based cell selection are compared. Results reveal that the adaptive CRE bias of the resource block utilization ratio (RBUR) technique exhibits the highest cell-edge throughput. Moreover, more accurate cell load estimation is obtained in the extended RBUR adaptive CRE bias technique through constant bit rate (CBR) traffic, which further improved load balancing as against the estimation based on the number of user equipment (UE). Finally, this paper presents suggestions for future research directions.

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Torres, R. P., S. Loredo, L. Valle, and M. Domingo. "An accurate and efficient method based on ray-tracing for the prediction of local flat-fading statistics in picocell radio channels." IEEE Journal on Selected Areas in Communications 19, no. 2 (2001): 170–78. http://dx.doi.org/10.1109/49.914495.

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Seo, Jongpil, Hyeonsu Kim, Jongmin Ahn, and Jaehak Chung. "Macrocell Protection Interference Alignment in Two-Tier Downlink Heterogeneous Networks." Mobile Information Systems 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/7410546.

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Conventional interference alignment (IA) has been developed to mitigate interference problems for the coexistence of picocells and macrocells. This paper proposes a macrocell protection interference alignment (MCP-IA) in two-tier MIMO downlink heterogeneous networks. The proposed method aligns the interference of the macro user equipment (UE) and mitigates the interference of the pico-UEs with a minimum mean squared error interference rejection combining (MMSE-IRC) receiver. Compared to the conventional IA, the proposed MCP-IA provides an additional array gain obtained by the precoder design of the macro BS and a diversity gain achieved by signal space selections. The degrees of freedom (DoF) of the proposed MCP-IA are equal to or greater than that of the conventional IA and are derived theoretically. Link level simulations show the link capacity and the DoF of the macro UE, and also exhibit the proposed MCP-IA attaining additional array gain and diversity gain. The system level simulation illustrates that the proposed method prevents the interference of the macro UE completely and preserves the throughput of the pico-UE irrespective of the number of picocells. For 4×2 antenna configuration, the system level simulation demonstrates that the proposed MCP-IA throughput of the macro UE is not affected by the number of picocells and that the proposed MCP-IA throughput of the picocells approaches that of single-user MIMO (SU-MIMO) with a 3% loss.

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Ting-Yu Lin and Yu-Chee Tseng. "Collision analysis for a multi-Bluetooth picocells environment." IEEE Communications Letters 7, no. 10 (2003): 475–77. http://dx.doi.org/10.1109/lcomm.2003.817313.

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Winters, Jack, Andrey Kobyakov, and Michael Sauer. "Picocells with MIMO and Cell Bonding for WLANs." IEEE Journal on Selected Areas in Communications 29, no. 6 (2011): 1164–71. http://dx.doi.org/10.1109/jsac.2011.110605.

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Kracek, Jan, and Milos Mazanek. "Possibilities of wireless power supply." International Journal of Microwave and Wireless Technologies 2, no. 2 (2010): 153–57. http://dx.doi.org/10.1017/s1759078710000255.

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This paper presents an overview of the principles suitable for wireless power supply of devices with a small power input in picocells. This means predominantly different types of small electric devices in the space of rooms. Basic principles, namely electromagnetic induction and electromagnetic wave, are explained using examples of developed systems. Different types of wireless power systems are compared with respect to efficiency, frequency, power, and transmission distance.

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