scholarly journals A Low-Complexity Resource Allocation for Multiple Access Passive IoT System

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1421
Author(s):  
Shiying Han ◽  
Zixiong Wang
Keyword(s):  
Resource Allocation ◽  
Optimization Problems ◽  
Low Complexity ◽  
Reflection Coefficients ◽  
Primary System ◽  
Adaptive Optimization ◽  
Transmit Power ◽  
Closed Form Solutions ◽  
Backscatter Communication

An ambient backscatter communication (AmBC) system with multiple backscatter devices (BDs) is investigated in this work. The cooperative reader receives the information from the primary transmitter (PT) and the multiple BDs simultaneously. With the asymptotic signal-to-noise-plus-interference ratio (SINR) of the BDs, an optimization problem that jointly optimizes the reflection coefficients of BDs and the primary transmit power is formulated. Considering that the adaptive optimization of reflection coefficients according to the instantaneous primary channel state information (CSI) is unaffordable in practice, we propose a low-complexity resource allocation scheme, which results in a long-term configuration of the BD reflection coefficients before the primary transmit power is allocated. With the long-term reflection coefficients, the transmit power of the primary system is optimized by solving the transformed two cascaded optimization problems which have closed-form solutions. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

scholarly journals Downlink and Uplink Cooperative Transmission for Primary Secrecy Based Cognitive Radio Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-14
Author(s):  
Dawei Wang ◽  
Pinyi Ren ◽  
Qinghe Du ◽  
Li Sun ◽  
Yichen Wang
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Optimization Problems ◽  
Transmission Rate ◽  
Cooperative Relaying ◽  
Cooperative Transmission ◽  
Primary System ◽  
Transmit Power ◽  
Cognitive Radio Sensor Networks ◽  
Secure Transmission

Aiming at allocating more licensed spectrum to wireless sensor nodes (SNs) under the constraint of the information security requirement of the primary system, in this paper, we propose a cooperative relaying and jamming secure transmission (CRJS) scheme in which SNs will relay primary message and jam primary eavesdrop concurrently with SN’s downlink and uplink information transmission in cognitive radio sensor networks (CRSNs). In our proposed CRJS scheme, SNs take advantages of physical layer secure technologies to protect the primary transmission and acquire some interference-free licensed spectrum as a reward. In addition, both decode-and-forward (DF) and amplify-and-forward (AF) relaying protocols are investigated in our proposed CRJS scheme. Our object is to maximize the transmission rate of SNs by optimal allocating of the relaying power, jamming power, and downlink and uplink transmit power under the target secure transmission rate requirement of the primary system. Moreover, two suboptimal algorithms are proposed to deal with these optimization problems. Furthermore, we analyze the transmission rate of SNs and allocate the relaying power, jamming power, and downlink and uplink transmit power for the asymptotic scenarios. Simulation results demonstrate the performance superiority of our developed strategy over conventional jamming scheme in terms of the transmission rate of WSN.

scholarly journals Suboptimal rate adaptive resource allocation in multiuser OFDM communication systems

2021 ◽  
Author(s):  
Sanam Sadr
Keyword(s):  
Resource Allocation ◽  
Power Allocation ◽  
Low Complexity ◽  
Adaptive Resource Allocation ◽  
Ofdm Systems ◽  
Transmit Power ◽  
Rate Adaptive ◽  
Adaptive Resource ◽  
Allocation Algorithms ◽  
Multiuser Ofdm

This thesis aims to study the performance of adaptive resource allocation in the downlink of multiuse OFDM systems with fixed or varialbe rate requirements (with fairness consideration) as well as low complexity algorithms for real-time implementations in practical systems. We first verify the simplifying assumption of flat transmit power over the entire bandwidth. Two different optimal and suboptimal power allocation schemes are applied in a single-user system and the decrease in the total throughput due to the presence of the power mask on subcarriers is measured. Based on the comparison of the achieved data rates, a flat transmit power is then assumed in the proposed suboptimal multiuser resource allocation algorithms. Two suboptimal resource allocation algorithms are then proposed using this simplifying assumption. The objective of the first algorithm is to maximize the total throughput while maintaining rate proportionality among the users. The proposed suboptimal algorithm prioritizes the user with the highest sensitivity to the subcarrier allocation and the variance over the subchannel gains is sued to define the sensitivity of each user. The second algorithm concerns rate adaptive resource allocation in multiuser OFDM systems with fixed rate constraints for each user. We propose a suboptimal joint subchannel and power allocation algorithm which attempts to maximize the total throughput wihile supporting the users with their minimum rate requirments. The main feature of this algorithm is its low complexity while achieving close to optimum capacity.

scholarly journals Resource Allocation in NOMA-Assisted Ambient Backscatter Communication System

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3061
Author(s):  
Qiang Liu ◽  
Songlin Sun ◽  
Jijiang Hou ◽  
Hongbiao Jia ◽  
Michel Kadoch
Keyword(s):  
Optimization Algorithm ◽  
Optimal Solution ◽  
Low Complexity ◽  
Optimal Number ◽  
Reflection Coefficients ◽  
Allocation Strategy ◽  
System A ◽  
Backscatter Communication ◽  
Grouping Strategy ◽  
Ambient Backscatter

This paper considers a non-orthogonal multiple access (NOMA)-assisted ambient backscatter communication (AmBC) system. To maximize the achievable sum rate (ASR) of the AmBC system, a joint optimization problem over a backscatter device (BD) grouping strategy, reflection coefficients, and decoding order is formulated, where the BD grouping strategy contains the number of BD groups and the BD allocation strategy. The BD grouping strategy, the reflection coefficients, and the decoding order are all intertwined, and the global search is extremely complex. As a result, we propose a four-step optimization algorithm. First, we give the closed-form optimal solution of the BD decoding order and reflection coefficient for a given grouping strategy. Then, for a given number of BD groups, we propose a low-complexity BD allocation strategy based on the complexity–performance trade-off. Finally, the number of BD groups with the largest ASR is selected as the global optimal number of BD groups. The simulation results show that the proposed four-step optimization algorithm is better than the benchmark solution.

scholarly journals Suboptimal rate adaptive resource allocation in multiuser OFDM communication systems

2021 ◽  
Author(s):  
Sanam Sadr
Keyword(s):  
Resource Allocation ◽  
Power Allocation ◽  
Low Complexity ◽  
Adaptive Resource Allocation ◽  
Ofdm Systems ◽  
Transmit Power ◽  
Rate Adaptive ◽  
Adaptive Resource ◽  
Allocation Algorithms ◽  
Multiuser Ofdm

This thesis aims to study the performance of adaptive resource allocation in the downlink of multiuse OFDM systems with fixed or varialbe rate requirements (with fairness consideration) as well as low complexity algorithms for real-time implementations in practical systems. We first verify the simplifying assumption of flat transmit power over the entire bandwidth. Two different optimal and suboptimal power allocation schemes are applied in a single-user system and the decrease in the total throughput due to the presence of the power mask on subcarriers is measured. Based on the comparison of the achieved data rates, a flat transmit power is then assumed in the proposed suboptimal multiuser resource allocation algorithms. Two suboptimal resource allocation algorithms are then proposed using this simplifying assumption. The objective of the first algorithm is to maximize the total throughput while maintaining rate proportionality among the users. The proposed suboptimal algorithm prioritizes the user with the highest sensitivity to the subcarrier allocation and the variance over the subchannel gains is sued to define the sensitivity of each user. The second algorithm concerns rate adaptive resource allocation in multiuser OFDM systems with fixed rate constraints for each user. We propose a suboptimal joint subchannel and power allocation algorithm which attempts to maximize the total throughput wihile supporting the users with their minimum rate requirments. The main feature of this algorithm is its low complexity while achieving close to optimum capacity.

scholarly journals Cost-Effective Optimization for Blockchain-Enabled NOMA-Based MEC Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jianbo Du ◽  
Yan Sun ◽  
Aijing Sun ◽  
Guangyue Lu ◽  
Zhixian Chang ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Power Control ◽  
Mobile Devices ◽  
Heuristic Algorithms ◽  
Cost Effective ◽  
Low Complexity ◽  
Spectrum Efficiency ◽  
User Association ◽  
Transmit Power ◽  
Transmit Power Control

Blockchain technology has been widely used in many fields. However, the proof of work (PoW) problem in the mining process of mobile devices requires a large amount of computing resources and energy consumption, which brings huge challenges to mobile devices. Mobile edge computing (MEC) can effectively solve the above problems, allowing mobile devices to offload tasks to edge servers to relieve the pressure of limited computing resources on mobile devices. Nonorthogonal multiple access (NOMA) is good at improving spectrum efficiency, so that the system can accommodate more users. In this paper, we propose a new NOMA-based MEC-enabled blockchain framework. Under the conditions of a given task execution deadline, the decision of offloading, local computing resource allocation, user clustering and admission control, and transmit power control is jointly optimized to minimize the total cost of the system. Since the problem is hard to solve, we decouple it into subproblems for low-complexity solutions. First, we propose two heuristic algorithms to obtain the binary offloading decision and user association, and then closed-form solutions of local resource allocation and transmit power control are obtained under the required delay constraints. Simulation results show that our proposed algorithms perform good in cost reduction compared with other baseline algorithms.

Low-Complexity Resource Allocation Algorithm for Multicell OFDMA System

2013 ◽  
Vol E96.B (5) ◽  
pp. 1218-1221 ◽  
Author(s):  
Qingli ZHAO ◽  
Fangjiong CHEN ◽  
Sujuan XIONG ◽  
Gang WEI
Keyword(s):  
Resource Allocation ◽  
Low Complexity ◽  
Ofdma System ◽  
Resource Allocation Algorithm ◽  
Allocation Algorithm

scholarly journals D2D Assisted Cellular Networks in Licensed and Unlicensed Spectrum: Matching-Iteration-Based Joint User Access and Resource Allocation

Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 80
Author(s):  
Qiuqi Han ◽  
Guangyuan Zheng ◽  
Chen Xu
Keyword(s):  
Resource Allocation ◽  
Cellular Networks ◽  
System Capacity ◽  
System Throughput ◽  
Unlicensed Spectrum ◽  
Resource Allocation Algorithm ◽  
User Access ◽  
Limited Spectrum

Device-to-Device (D2D) communications, which enable direct communication between nearby user devices over the licensed spectrum, have been considered a key technique to improve spectral efficiency and system throughput in cellular networks (CNs). However, the limited spectrum resources cannot be sufficient to support more cellular users (CUs) and D2D users to meet the growth of the traffic data in future wireless networks. Therefore, Long-Term Evolution-Unlicensed (LTE-U) and D2D-Unlicensed (D2D-U) technologies have been proposed to further enhance system capacity by extending the CUs and D2D users on the unlicensed spectrum for communications. In this paper, we consider an LTE network where the CUs and D2D users are allowed to share the unlicensed spectrum with Wi-Fi users. To maximize the sum rate of all users while guaranteeing each user’s quality of service (QoS), we jointly consider user access and resource allocation. To tackle the formulated problem, we propose a matching-iteration-based joint user access and resource allocation algorithm. Simulation results show that the proposed algorithm can significantly improve system throughput compared to the other benchmark algorithms.

scholarly journals When Scarcity Meets Disparity: “Resources Allocation and COVID-19 Patients with Diabetes”

2021 ◽  
pp. 193229682199111
Author(s):  
Jacob M. Appel
Keyword(s):  
Risk Factors ◽  
Resource Allocation ◽  
Life Expectancy ◽  
Ethical Challenge ◽  
Severe Illness ◽  
Resources Allocation ◽  
Economic Disparity ◽  
Patients With Diabetes ◽  
Current Stage

The COVID-19 pandemic raised distinct challenges in the field of scarce resource allocation, a long-standing area of inquiry in the field of bioethics. Policymakers and states developed crisis guidelines for ventilator triage that incorporated such factors as immediate prognosis, long-term life expectancy, and current stage of life. Often these depend upon existing risk factors for severe illness, including diabetes. However, these algorithms generally failed to account for the underlying structural biases, including systematic racism and economic disparity, that rendered some patients more vulnerable to these conditions. This paper discusses this unique ethical challenge in resource allocation through the lens of care for patients with severe COVID-19 and diabetes.

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