Unmanned Aerial Vehicles (UAV) deployed in the air can be used as base stations (BSs) to provide uplink and downlink transmissions for ground cellular users in a target area. This paper considers the coverage recovery...
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ISBN:
(纸本)9781728182988
Unmanned Aerial Vehicles (UAV) deployed in the air can be used as base stations (BSs) to provide uplink and downlink transmissions for ground cellular users in a target area. This paper considers the coverage recovery problem in a cellular network with UAVs as base stations when one or more UAVs go offline due to energy replenishment or extreme environment. A coverage analysis of the target area is first presented in order to obtain the condition on the coverage radius of a UAV BS (UBS) for producing a full coverage of the target area. In the case of UAV offline, the coverage radius of a UBS needs to be adjusted to recover the full coverage of the target area, which can be implemented by adjusting either the altitude or the transmission power of the UBS. Based on the obtained full coverage condition on the UBS coverage radius, a coverage recovery analysis is further presented for determining the adjustment range of the altitude or transmission power of a UBS. For this purpose, the relationship between the coverage radius and the altitude and that between the coverage radius and the transmission power are analyzed. Through numerical results, it is demonstrated that the full coverage of a target area can effectively be recovered by adjusting either the altitude or transmission power of a UBS in the case of UBS offline.
The fifth-generation (5G) wireless technology is primarily designed to address a wide range of use cases categorized into the enhanced mobile broadband (eMBB), ultra-reliable and low latency communication (URLLC), and...
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The fifth-generation (5G) wireless technology is primarily designed to address a wide range of use cases categorized into the enhanced mobile broadband (eMBB), ultra-reliable and low latency communication (URLLC), and massive machine-type communication (mMTC). Nevertheless, there are a few other use cases that are in-between these main use cases such as industrial wireless sensor networks, video surveillance, or wearables. In order to efficiently serve such use cases, in Release 17, the 3rd generation partnership project (3GPP) introduced the reduced capability NR devices (NR-RedCap) with lower cost and complexity, smaller form factor, and longer battery life compared to regular NR devices. However, one key potential consequence of device cost and complexity reduction is coverage loss. In this paper, we provide a comprehensive evaluation of NR RedCap coverage for different physical channels and initial access messages to identify the channels/messages that are potentially coverage limiting for RedCap UEs. We perform the coverage evaluations for RedCap UEs operating in three different scenarios, namely Rural, Urban and Indoor with carrier frequencies 0.7 GHz, 2.6 GHz and 28 GHz, respectively. Our results confirm that for all the considered scenarios, the amounts of required coverage recovery for RedCap channels are either less than 1 dB or can be compensated by considering smaller data rate targets for RedCap use cases.
Wireless Sensor Networks (WSNs) are the key part of Internet of Things, as they provide the physical interface between on field information and backbone analytic engines. An important role of WSNs-when collecting vita...
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ISBN:
(纸本)9781740523905
Wireless Sensor Networks (WSNs) are the key part of Internet of Things, as they provide the physical interface between on field information and backbone analytic engines. An important role of WSNs-when collecting vital information-is to provide a consistent and reliable coverage. To Achieve this, WSNs must implement a highly reliable and efficient coverage recovery algorithm. In this paper, we take a fresh new approach to coverage recovery based on evolutionary algorithms. We propose EMACB-SA, which introduces a new evolutionary algorithm that selects coverage sets using a fitness function that balances energy efficiency and redundancy. The proposed algorithm improves network's coverage and lifetime in areas with heterogeneous event rate in comparison to previous works and hence, it is suitable for using in disaster management.
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