# Novel SWIPT Schemes for 5G Wireless Networks

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## Abstract

**:**

## 1. Introduction

## 2. Motivation for an Energy-Efficient 5G Network

## 3. Case Study 1: Wireless Power Transfer-Enabled Data Rate Fairness Beamforming

#### Numerical Results

## 4. Case Study 2: Built-In Energy-Efficient Modulation-Based NOMA

#### 4.1. Proposals for SWIPT-Enabled M-NOMA

#### 4.2. M-NOMA Communication

#### 4.3. M-NOMA: An Efficient System

## 5. Case Study 3: Receiver Designing to Employ SWIPT with Joint CFO and Channel Estimation

#### 5.1. System Model

- Estimate CFO of ${Y}_{k,l,i}^{(\Delta f)}$ by using the Moose technique [29]. The mean CFO estimate is more accurate with the increase in the number of signal blocks. Compensate the CFO of ${Y}_{k,l,i}^{(\Delta f)}$ with the mean CFO estimate value.
- Compute the average channel estimate over l blocks, and compute the information estimate using the average channel estimate.
- To improve the accuracy of the decoding process, the IB-DFE receiver was used to improve the information estimates, and again, the information estimates were recursively used to improve the channel estimate in a feedback loop, as in [37].

#### 5.2. Numerical Results

## 6. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 3.**Comparison of data rates at DUs for the considered systems and beamforming techniques with the total power available at PBs. EH, energy harvesting; SMAPB, single multiple antenna PB.

**Figure 5.**Harvested energy vs. distance for BEEM-NOMA (M-U1) and NOMA (U1) with energy efficiency ${\eta}_{ee}=60\%$. BEEM-NOMA outperforms NOMA.

**Figure 6.**Harvested energy vs. transmit power for BEEM-NOMA (M-U1, M-U2, M-U3, and M-U4) and NOMA (U1, U2, U3, and U4).

**Figure 7.**Block diagram of the receiver for SWIPT with joint carrier frequency offset (CFO) and channel estimation. SC-FDMA, single-carrier frequency-division multiple access; IB-DFE, iterative block decision feedback equalization.

**Figure 8.**Comparison of the BER performance of the system based on two different methods to estimate information.

**Figure 9.**BER performance based on the ratio of the power between the pilot signal and the information in the superimposed signal.

**Table 1.**Assessment of the individual energy-harvesting capability of NOMA and BEEM-NOMA. SIC, successive interference cancellation.

System Evaluation | Receiver | U1 | U2 | U3 | U4 |
---|---|---|---|---|---|

Decode | NOMA | U1, U2, U3 and U4 | U2, U3 and U4 | U3 and U4 | U4 |

M-NOMA | U1 and U2 | U2 | U3 and U4 | U4 | |

SIC | NOMA | U2, U3, and U4 | U3 and U4 | U4 | N/A |

M-NOMA | U2 | N/A | U4 | N/A | |

Interference cancellation | NOMA | No | No | No | With U1, U2, and U3 |

M-NOMA | No | No | No | With U3 only | |

Energy-harvested signals | NOMA | Power splitting of U1’s, U2’s, U3’s, and U4’s signals | Power splitting of U1’s, U2’s, U3’s, and U4’s signals | Power splitting of U1’s, U2’s, U3’s, and U4’s signals | Power splitting of U1’s, U2’s, U3’s, and U4’s signals |

M-NOMA | Power splinting of U1’s and U2’s signals and directly without power splitting from U3’s and U4’s signals | Power splitting of U1’s and U2’s signals and directly without power splitting from U3’s and U4’s signals | Power splitting of U3’s and U4’s signals and directly without power splitting from U1’s and U2’s signals | Power splitting of U3’s and U4’s signals and directly without power splitting from U1’s and U2’s signals |

**Table 2.**The amount of energy harvested at the receiver and the expected value of the information estimate error based on the power of the pilot signal.

${\mathbf{P}}_{\mathbf{q}}$ (dBm) | 15 | 16 | 17 | 18 | 19 | 20 | 21 |
---|---|---|---|---|---|---|---|

${P}_{si}$ (dBm) | 25.4139 | 25.5150 | 25.6389 | 25.7901 | 25.9732 | 26.1933 | 26.4554 |

EH (mJ) | 0.0216 | 0.0221 | 0.0227 | 0.0235 | 0.0245 | 0.0258 | 0.0274 |

$\mathbb{E}[{{\epsilon}_{X}}_{k,l,F}^{(j,\Delta f)}]$ at 5 dB SNR | 0.2756 | 0.2105 | 0.1815 | 0.1594 | 0.1559 | 0.1525 | 0.1411 |

$\mathbb{E}[{{\epsilon}_{X}}_{k,l,F}^{(j,\Delta f)}]$ at 10 dB SNR | 0.0176 | 0.0143 | 0.0138 | 0.0138 | 0.0137 | 0.0138 | 0.0137 |

$\mathbb{E}[{{\epsilon}_{X}}_{k,l,F}^{(j,\Delta f)}]$ at 15 dB SNR | 0.0136 | 0.0135 | 0.0135 | 0.0135 | 0.0135 | 0.0135 | 0.0135 |

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**MDPI and ACS Style**

Rajaram, A.; Khan, R.; Tharranetharan, S.; Jayakody, D.N.K.; Dinis, R.; Panic, S.
Novel SWIPT Schemes for 5G Wireless Networks. *Sensors* **2019**, *19*, 1169.
https://doi.org/10.3390/s19051169

**AMA Style**

Rajaram A, Khan R, Tharranetharan S, Jayakody DNK, Dinis R, Panic S.
Novel SWIPT Schemes for 5G Wireless Networks. *Sensors*. 2019; 19(5):1169.
https://doi.org/10.3390/s19051169

**Chicago/Turabian Style**

Rajaram, Akashkumar, Rabia Khan, Selvakumar Tharranetharan, Dushantha Nalin K. Jayakody, Rui Dinis, and Stefan Panic.
2019. "Novel SWIPT Schemes for 5G Wireless Networks" *Sensors* 19, no. 5: 1169.
https://doi.org/10.3390/s19051169