1. Introduction

Radio-frequency (RF) energy harvesting (EH), abbreviated as RF-EH, enabled wireless power transfer (WPT) is an emerging and promising approach to supply everlasting and cost-effective energy to low-power electronic devices, that is, sensor nodes, low-power cellphone, wireless control devices, and so on [1–3]. This approach is expected to have abundant applications in next-generation wireless networks, such as Internet-of-Things (IoT) wireless networks or 5G networks, which can be a platform for varied fields, for example, manufacturing [4, 5], smart agriculture [5], and smart city [5]. Specifically, the IoT-based wireless sensor networks for smart agriculture usually consist of a large number of battery-powered wireless sensor nodes for data collecting, data processing, and data transmission. Therefore, these energy-constrained devices need to be replaced or recharged periodically; this leads the lifetime of network limited. The RF energy harvesting

can prolong the lifetime of these networks using the energy harvested from the RF sources (e.g., base station, TV/radio broadcast station, microwave station, satellite earth station, etc.). Compared with other resources available for the EH, the RF power is easy to be converted. Therefore, RF energy harvesting is the solution to enhance the system energy efficiency in the energy-constrained networks, including network lifetime; reduction of carbon footprint, without requiring battery replacement; easy and fast deployment in complicated or toxic environments; etc. In the past few years, there have been a number of works on RF energy harvesting communications, and the main works focused on the development of energy harvesting models, protocols, transmission schemes, and security in communication systems [1–3]. In practice, RF-EH can be operated in a time switching (TS) scheme in which the receiver uses a portion of time duration for energy harvesting and the remaining time for information receiving or a power splitting (PS) scheme in which the received signal power is divided into two parts for energy harvesting and information receiving, separately [6].

harvested energy varies according to channel fading, and the energy usage overtime

Performance Analysis for NOMA Relaying System in Next-Generation Networks with RF Energy…

The next-generation networks (5G and beyond) are supported with very high data rate, ultralow latency, massive connections, and very high mobility to satisfy the fast-increasing users and demands. To fulfill these targets, the relaying and nonorthogonal multiple access (NOMA) techniques are proposed to extend the coverage of network, improve the performance, achieve high spectral efficiency, and support dense networks [11]. In NOMA scheme, the source superposes all messages before transmitting them to users as Figure 2. In this figure, we can see that the near receiver (or better user) uses successive interference cancelation (SIC) to obtain the far user's message first (due to it is allocated with more transmit power) and subtracts this component from the received signal to obtain its own message. Compared to conventional orthogonal multiple access (OMA), for example, frequency division multiple access (FDMA), time division multiple access (TDMA), and code division multiple access (CDMA), NOMA simultaneously serves multiple user equipment on the same resource blocks by splitting users into power domain

needs to make a tradeoff between energy harvesting time and information

[11]; therefore it can improve spectral efficiency of wireless network.

transmit RF energy and information by using TS or PS scheme.

for this considered system.

Figure 2.

105

Illustration of NOMA.

The above three techniques (i.e., RF-EH, relaying, NOMA) can be integrated into next-generation networks. However, there are many related issues that need to be addressed before these techniques can be deployed in next-generation networks, such as the network architecture, power allocation, relaying scheme selection, the combination between NOMA and other multiple access methods, fixed or dynamic user pairing/clustering, optimal user allocation and beamforming in NOMA MIMO systems, the impact of imperfect CSI, and joint optimization of diverse aspects of NOMA (spectrum efficiency, energy efficiency, security) [11]. In recent years, a number of works investigated some related issues such as performance of energy harvesting DF/AF relaying, cooperative, cognitive, and MIMO NOMA networks [12–15]. In addition, the work of [16] studied the secrecy performance of MIMO NOMA system over Nakagami-m channels with transmit antenna selection protocol. However, almost in these works the information sources are assumed that it can

Different from the above works, in this chapter we investigate the cooperative NOMA network in which the power station and information source (e.g., base station) are separated and the energy-constrained user nodes collaborate with the

• The triple-phase harvest-transmit-forward transmission protocol is proposed

energy-constrained relay nodes to help source forward the information to destinations. The main contributions of this chapter are as follows:

processing time.

DOI: http://dx.doi.org/10.5772/intechopen.89253

Relaying communication technique can mitigate the wireless channel fading and improve the reliability of wireless links by exploiting the spatial diversity gains inherent in multiple user environments [7]. This can be achieved by using collaboration of relay nodes to form virtual multiple input multiple output (MIMO) without the need of multiple antennas at each node. Figure 1 depicts a system model of cooperative network. We can observe from this figure that the destination D can receive two signals from direct link and relaying link. It means that D has more opportunities to decode its own message; thus the performance of this system can be improved. There are two schemes of relaying technique: amplify-and-forward (AF) or decode-and-forward (DF). In AF relaying scheme, the relay simply sends a scaled copy of the received noisy signal to the destination, while in DF relaying scheme, the relay transmits a re-encoded copy to the destination, if the relay can successfully decode the transmitted message. In wireless relaying networks (e.g., energy-constrained wireless sensor networks), the relay nodes (e.g., cluster head nodes) are often subject to space limitation to equip a large battery for long lifetime using [8]. Thus, RF energy harvesting technique has been applied for this type of relay nodes to not only improve the throughput and reliability by exploiting the virtual spatial diversity but also promise everlasting network lifetime without requiring battery replacement. Due to the new imposed time-varying energy constraints, several technical issues, such as relaying protocols, power allocation, energy-information tradeoff, relay selection, cooperative spectrum sensing and sharing, security, etc., have been investigated for various relaying network models [6, 9, 10]. The challenges in these works become more complicated because the

Figure 1. A system model of cooperative network.

Performance Analysis for NOMA Relaying System in Next-Generation Networks with RF Energy… DOI: http://dx.doi.org/10.5772/intechopen.89253

harvested energy varies according to channel fading, and the energy usage overtime needs to make a tradeoff between energy harvesting time and information processing time.

The next-generation networks (5G and beyond) are supported with very high data rate, ultralow latency, massive connections, and very high mobility to satisfy the fast-increasing users and demands. To fulfill these targets, the relaying and nonorthogonal multiple access (NOMA) techniques are proposed to extend the coverage of network, improve the performance, achieve high spectral efficiency, and support dense networks [11]. In NOMA scheme, the source superposes all messages before transmitting them to users as Figure 2. In this figure, we can see that the near receiver (or better user) uses successive interference cancelation (SIC) to obtain the far user's message first (due to it is allocated with more transmit power) and subtracts this component from the received signal to obtain its own message. Compared to conventional orthogonal multiple access (OMA), for example, frequency division multiple access (FDMA), time division multiple access (TDMA), and code division multiple access (CDMA), NOMA simultaneously serves multiple user equipment on the same resource blocks by splitting users into power domain [11]; therefore it can improve spectral efficiency of wireless network.

The above three techniques (i.e., RF-EH, relaying, NOMA) can be integrated into next-generation networks. However, there are many related issues that need to be addressed before these techniques can be deployed in next-generation networks, such as the network architecture, power allocation, relaying scheme selection, the combination between NOMA and other multiple access methods, fixed or dynamic user pairing/clustering, optimal user allocation and beamforming in NOMA MIMO systems, the impact of imperfect CSI, and joint optimization of diverse aspects of NOMA (spectrum efficiency, energy efficiency, security) [11]. In recent years, a number of works investigated some related issues such as performance of energy harvesting DF/AF relaying, cooperative, cognitive, and MIMO NOMA networks [12–15]. In addition, the work of [16] studied the secrecy performance of MIMO NOMA system over Nakagami-m channels with transmit antenna selection protocol. However, almost in these works the information sources are assumed that it can transmit RF energy and information by using TS or PS scheme.

Different from the above works, in this chapter we investigate the cooperative NOMA network in which the power station and information source (e.g., base station) are separated and the energy-constrained user nodes collaborate with the energy-constrained relay nodes to help source forward the information to destinations. The main contributions of this chapter are as follows:

• The triple-phase harvest-transmit-forward transmission protocol is proposed for this considered system.

Figure 2. Illustration of NOMA.

can prolong the lifetime of these networks using the energy harvested from the RF sources (e.g., base station, TV/radio broadcast station, microwave station, satellite earth station, etc.). Compared with other resources available for the EH, the RF power is easy to be converted. Therefore, RF energy harvesting is the solution to enhance the system energy efficiency in the energy-constrained networks, including network lifetime; reduction of carbon footprint, without requiring battery replacement; easy and fast deployment in complicated or toxic environments; etc. In the past few years, there have been a number of works on RF energy harvesting communications, and the main works focused on the development of energy harvesting models, protocols, transmission schemes, and security in communication systems [1–3]. In practice, RF-EH can be operated in a time switching (TS) scheme in which the receiver uses a portion of time duration for energy harvesting and the remaining time for information receiving or a power splitting (PS) scheme in which the received signal power is divided into two parts for energy harvesting

Relaying communication technique can mitigate the wireless channel fading and

improve the reliability of wireless links by exploiting the spatial diversity gains inherent in multiple user environments [7]. This can be achieved by using collaboration of relay nodes to form virtual multiple input multiple output (MIMO) without the need of multiple antennas at each node. Figure 1 depicts a system model of cooperative network. We can observe from this figure that the destination D can receive two signals from direct link and relaying link. It means that D has more opportunities to decode its own message; thus the performance of this system can be improved. There are two schemes of relaying technique: amplify-and-forward (AF) or decode-and-forward (DF). In AF relaying scheme, the relay simply sends a scaled copy of the received noisy signal to the destination, while in DF relaying scheme, the relay transmits a re-encoded copy to the destination, if the relay can successfully decode the transmitted message. In wireless relaying networks (e.g., energy-constrained wireless sensor networks), the relay nodes (e.g., cluster head nodes) are often subject to space limitation to equip a large battery for long lifetime using [8]. Thus, RF energy harvesting technique has been applied for this type of relay nodes to not only improve the throughput and reliability by exploiting the virtual spatial diversity but also promise everlasting network lifetime without requiring battery replacement. Due to the new imposed time-varying energy constraints, several technical issues, such as relaying protocols, power allocation, energy-information tradeoff, relay selection, cooperative spectrum sensing and sharing, security, etc., have been investigated for various relaying network models [6, 9, 10]. The challenges in these works become more complicated because the

and information receiving, separately [6].

Recent Wireless Power Transfer Technologies

Figure 1.

104

A system model of cooperative network.


The scenario of this considered system is investigated as follows:

The triple-phase protocol for RF-EH NOMA relaying network.

DOI: http://dx.doi.org/10.5772/intechopen.89253

mode.

Figure 4.

and the same variance σ<sup>2</sup>

each transmission).

2.1 Power transfer phase

respectively expressed as

107

transmit superimposed message signal

• Due to the severe shadowing environment, the worse node (i.e., Dn) cannot detect message signal transmitted from S. Thus, the better node (i.e., Dm) or relay node R is selected to help S forwarding the message signal to worse node.

Performance Analysis for NOMA Relaying System in Next-Generation Networks with RF Energy…

• All the transceivers are equipped by single antenna and operate in half duplex

• All wireless links are assumed to undergo independent frequency nonselective

• The power gains of all links are modeled by random variables with zero mean

In this work, we propose a triple-phase harvest-transmit-forward transmission

1. In the first phase (power transfer phase): P transfers RF energy to the users with power P<sup>0</sup> in the time αT (0 ≤ α ≤ 1, time switching ratio; T, block time for

2. In the second phase (information transmitting phase): S uses power PS to

to user pair (Dm, Dn) in the time of (1�α)T/2, where sm and sn are the message for the mth user Dm and the nth user Dn, respectively, and am and an are the power allocation coefficients which satisfied the conditions: 0 < am < an and am + an = 1 by following the NOMA scheme. By applying NOMA, Dm uses SIC to detect message sn and subtracts this component from the received signal to obtain its own message sm.

3. In the third phase (information relaying phase): in this phase, Dm re-encodes and forwards sn to Dn in the remaining time of (1�α)T/2 with the energy harvested from P. At the same time, relay decodes x and forwards x to Dn.

Finally, Dn combines two received signals, that is, the relaying signals from Dm

In this phase, the energy of Dm and R harvested from P in the time of αT can be

and R, to decode its own message by using selection combining (SC) scheme. For more detailed purpose, we continue to present the transmission of this

protocol for RF-EH NOMA relaying system in mathematical manner.

<sup>x</sup> <sup>¼</sup> ffiffiffiffiffiffi am <sup>p</sup> sm <sup>þ</sup> ffiffiffiffiffi

).

an

<sup>p</sup> sn (1)

Rayleigh block fading and additive white Gaussian noise (AWGN).

, that is, �CN(0,σ<sup>2</sup>

protocol for this RF-EH NOMA relaying system as shown in Figure 4:
