Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT
<p>Dual hop system with a PR and/or AR device.</p> "> Figure 2
<p>Comparison between the energy extraction capabilities of linear and non-linear energy harvesting models.</p> "> Figure 3
<p>Performance analysis of the weighted utility function for (<b>a</b>) PS scheme, and (<b>b</b>) TS scheme; versus the maximum limitation on the total transmit power.</p> "> Figure 4
<p>Analysis of harvested energy for PS and TS schemes versus the demanded data (R-E trade-off).</p> "> Figure 5
<p>Performance analysis of the weighted utility function for (<b>a</b>) PS scheme, and (<b>b</b>) TS scheme; versus the variation in the (fixed) TSF <math display="inline"><semantics> <mstyle> <mi>δ</mi> </mstyle> </semantics></math>, while comparing HAP, AGN and PGN</p> "> Figure 6
<p>Analysis of harvested energy for (<b>a</b>) PS scheme, and (<b>b</b>) TS scheme; versus the demanded data (R-E trade-off) with error bars pertaining to a confidence level of 95%.</p> ">
Abstract
:1. Introduction
1.1. General Motivation
1.2. Background to the Considered Topics
1.3. Related Works
1.4. Our Contributions
- (i)
- In contrast to the existing reflector-only and relaying-only techniques, we propose a novel hybrid active-and-passive relaying scheme to facilitate SWIPT to a PS- or TS-enabled end-user, along with the dynamic designing of dual-hop TP, under certain receive processing assumptions.
- (ii)
- We formulate a novel problem (incorporating the three systems) to maximize the weighted utility function comprising data throughput, harvested energy and transmit power, subjected to some quality-of-service (QoS) constraints. Unlike the other works that assume equal time-intervals in the two hops (also considered herein as the benchmarks), we present a framework to dynamically design the TP for the dual-hop link, along with the computation of the PS or TS factors.
- (iii)
- In order to solve the aforementioned problems, we present two distinct methods based on the Lagrange dual technique and Dinkelbach method assisted convex programming, respectively, where both the approaches yield an appreciable solution within polynomial computational-time.
- (iv)
- The effectiveness of the proposed hybrid active-and-passive relaying scheme is shown over the reflector-only and relay-only schemes for both PS and TS SWIPT schemes via numerical analysis, with individual benefits shown over their respective benchmark designs having a fixed TP.
1.5. Further Organization of the Paper
2. System Model
3. Analysis of Greencom Network Scenarios
3.1. Traditional Passive Repeater or Active Relay-Based Systems
3.2. Proposed Hybrid Active-and-Passive Relaying Scheme
4. Problem Formulation and Solution
4.1. Variable Definitions to Assist the Problem Formulation
4.2. Optimization Problem with Weighted Utility Function
4.3. Proposed Solutions to the Above-Mentioned Problem
4.3.1. Method to Seek an Asymptotically Optimal Solution
4.3.2. Dinkelback Method Assisted Convex Programming
Algorithm 1 Dinkelbach-assisted Alternating Parameter Optimization |
|
5. Numerical Results
5.1. Simulation Set-Up
5.2. Experimental Findings and Analysis
5.3. General Outcomes and Trailing Discussion
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Acronym | Full-Form |
---|---|
3GPP | 3rd Generation Partnership Project |
5G | Fifth Generation Mobile Wireless Communications |
6G | Sixth Generation Mobile Wireless Communications |
AF | Amplify-and-Forward |
AGN | Active Relay Device-based Green Communication Network |
AR | Active Relay |
AWGN | Additive White Gaussian Noise |
CSI | Channel State Information |
DCCP | Disciplined Convex-Concave Programming |
DF | Decode-and-Forward |
EH | Energy Harvesting |
FR1 | Frequency Range-1 for 5G |
FR2 | Frequency Range-2 for 5G |
Greencom | Green Communications |
HAP | Hybrid Active-and-Passive |
ID | Information Decoding |
IoT | Internet-of-Things |
IRS | Intelligent Reflecting Surface |
KKT | Karush-Kuhn-Tucker |
MRC | Maximum Ratio Combining |
NR | New Radio |
PGN | Passive Repeater Device-based Green Communication Network |
PR | Passive Repeater |
PS | Power Splitting |
QoS | Quality-of-Service |
RIS | Reconfigurable Intelligent Surface |
SNR | Signal-to-Noise-Ratio |
SWIPT | Simultaneous Wireless Information and Power Transfer |
TP | Time Period |
TS | Time Switching |
TSF | Time-Splitting Factor |
Notation | Definition |
---|---|
a | Coefficient associated with increase of path loss with distance |
Overall bandwidth | |
b | Coefficient associated with the offset value of path-loss |
c | Coefficient associated with increase of path loss with frequency |
d | Distance between the transmitting and receiving stations (in meters) |
Maximum harvested energy obtained on the saturation of the EH circuit | |
Non-linear EH (sigmoidal) expression with input power x | |
Non-linear EH expression for PS scheme | |
Non-linear EH expression for TS scheme | |
Harvested energy at the end-user with PS scheme in the PGN/AGN scenario | |
Harvested energy at the end-user with TS scheme in the PGN/AGN scenario | |
Parameter to refer to or according to the chosen scheme | |
Overall harvested energy at the end-user with PS scheme in the HAP scenario | |
Overall harvested energy at the end-user with TS scheme in the HAP scenario | |
Parameter to refer to or according to the chosen scheme | |
Expectation value operator | |
f | Operational frequency of the system |
Channel coefficient for the direct link between transmit source and end-user | |
Channel coefficient for the first phase of indirect link pertaining to PR device | |
Channel coefficient for the first phase of indirect link pertaining to AR device | |
Parameter to refer to or according to the chosen scheme | |
Channel coefficient for the second phase of indirect link pertaining to PR device | |
Channel coefficient for the second phase of indirect link pertaining to AR device | |
Parameter to refer to or according to the chosen scheme | |
Lagrange Dual Function | |
Lagrangian function operator | |
n | AWGN introduced at the PR device |
n | AWGN introduced at the AR device |
Parameter to refer to or according to the chosen scheme | |
AWGN introduced due to the antenna element of the end-user | |
The noise introduced by the baseband processing circuit at the end-user | |
Transmit power at the source | |
Maximum overall power available at the relay | |
Overall power limitation for the transmitter-relay system | |
Data throughput at the end-user with PS scheme in the PGN/AGN scenario | |
Data throughput at the end-user with TS scheme in the PGN/AGN scenario | |
Parameter to refer to or according to the chosen scheme | |
Overall data throughput at the end-user with PS scheme in the HAP scenario | |
Overall data throughput at the end-user with TS scheme in the HAP scenario | |
Parameter to refer to or according to the chosen scheme | |
Data throughput at the end-user with PS scheme via direct link | |
Data throughput at the end-user with TS scheme via direct link | |
Parameter to refer to or according to the chosen scheme | |
Transmit signal seen at the PR device | |
Transmit signal seen at the AR device | |
Parameter to refer to or according to the chosen scheme | |
s | Symbol tranmsitted from the source |
T | Time period |
w | Complex amplification coefficient of the AR device |
Signal received by the end-user via direct link | |
Signal received by the end-user via PR device over the second phase | |
Signal received by the end-user via AR device over the second phase | |
Parameter to refer to or according to the chosen scheme |
Symbol | Definition |
---|---|
Constants corresponding to the capacitor and diode turn-on voltage at EH circuit | |
Mean corresponding to the confidence interval formula | |
Time splitting factor corresponding to TP | |
Threshold limit corresponding to Algorithm 1 | |
Reflection efficiency coefficient of the PR device | |
Z-value corresponding to the confidence interval formula | |
Parameter to compute the intermediary fraction during the Dinkelbach process | |
Vector corresponding to the Lagrange dual variables: | |
The number of observations corresponding to the confidence interval formula | |
Weighing coefficient corresponding to the harvested energy | |
Weighing coefficient corresponding to the transmit power | |
Weighing coefficient corresponding to the data throughput | |
Power splitting ratio | |
Standard deviation | |
Noise variance corresponding to | |
Noise variance corresponding to | |
Noise variance corresponding to | |
Noise variance corresponding to | |
Parameter to refer to or according to the chosen scheme | |
Time-switching ratio | |
Metric to represent or interchangeably | |
SNR obtained at the end-user with PS scheme via direct link | |
SNR obtained at the end-user with TS scheme via direct link | |
SNR estimated at the PR via first hop indirect link | |
SNR estimated at the AR via first hop indirect link | |
Parameter to refer to or according to the chosen scheme | |
SNR obtained at the end-user with PS scheme via second hop PR device link | |
SNR obtained at the end-user with TS scheme via second hop PR device link | |
SNR obtained at the end-user with PS scheme via second hop AR device link | |
SNR obtained at the end-user with TS scheme via second hop AR device link | |
Parameter to refer to or according to the chosen scheme | |
Parameter to refer to or according to the chosen scheme | |
Minimum demanded data throughput | |
Minimum demanded harvested energy | |
Metric combining reflection/amplification coefficients of PR/AR, respectively |
Parameter | P | |||||
---|---|---|---|---|---|---|
System | ||||||
PGN | ||||||
AGN | ||||||
HAP |
Percentage | 80% | 85% | 90% | 95% | 99% | 99.5% | 99.9% |
---|---|---|---|---|---|---|---|
Z-value | 1.282 | 1.440 | 1.645 | 1.960 | 2.576 | 2.807 | 3.291 |
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Gautam, S.; Solanki, S.; Sharma, S.K.; Chatzinotas, S.; Ottersten, B. Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT. Sensors 2021, 21, 6013. https://doi.org/10.3390/s21186013
Gautam S, Solanki S, Sharma SK, Chatzinotas S, Ottersten B. Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT. Sensors. 2021; 21(18):6013. https://doi.org/10.3390/s21186013
Chicago/Turabian StyleGautam, Sumit, Sourabh Solanki, Shree Krishna Sharma, Symeon Chatzinotas, and Björn Ottersten. 2021. "Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT" Sensors 21, no. 18: 6013. https://doi.org/10.3390/s21186013
APA StyleGautam, S., Solanki, S., Sharma, S. K., Chatzinotas, S., & Ottersten, B. (2021). Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT. Sensors, 21(18), 6013. https://doi.org/10.3390/s21186013