whereM,a,bare the constant diode parameters, andPRFandPDCare the input RF power and
the output DC power, respectively. Then an optimal resource allocation problem is considered for a multi-user simultaneous wireless information and power transfer system based on the non-linear model.
There are another two commonly considered simplified models for RF-DC power conver- sion, as illustrated in Figs. 1.4(a) and (b) [34].
(i) For the near-practical model (Fig. 1.4(b)), the converted DC power is assumed to increase linearly with the received RF power only if it passes a threshold [35, 36].
(ii) For the ideal model (Fig. 1.4(c)), the converted DC power is assumed to be proportional to the RF power only if it is beyond the threshold [7, 26].
1.2.2.2 Network Model Based on WPT
There are three network models for WPT.
1. WPT only network, where energy transfer is in the downlink. In [37], the authors pro- posed a power beacon based hybrid cellular network. In the network, mobile users are wirelessly powered by randomly deployed power beacons, which enables mobile users
I V I=Is eγV−1 Is: saturation current γ: reciprocal of the thermal voltage PRF PDC Pth 0 PRF PDC Pth 0
(a) Accurate non-linear behaviour of the Schottky diode
(b) Near-practical approximation (c) Ideal approximation
Figure 1.4:Illustration of the models for RF-DC converter.
to have a much longer lifetime without battery replacement. The outage and coverage probability with power beacons was analyzed in [38].
Different scenarios such as single-/multi-user, relays, multi-carrier have been considered with WPT [7, 39, 40, 41, 42, 31, 43, 32].
In [7], wirelessly power transfer from a multi-antenna PB to single/multiple energy re- ceivers is studied, where the optimal WPT strategy are obtained. In [39], a system con- sisting of a single power beacon and multiple energy receivers was considered, where the energy receiver can only do one-bit feedback. The optimal channel learning algo- rithm was also proposed for such a WPT system. In [40], the distributed WPT system with limited-feedback was studied, where a distributed channel learning method was proposed. In [41], WPT-based sensor networks were considered, where a large-scale sensor network are powered by randomly deployed power beacons. The sensor-active probability was also studied.
In [42], the multiple power beacon placement problem was considered. The location of the power beacons was optimized which maximized the WPT powered communication network. In [31] and [43], WPT-based single- and bi-directional relay networks were considered, respectively, where the relay is wirelessly powered by the transmitter for relaying the information to the destination. The maximal throughput of such a relay
Energy Receiver Information Receiver Energy Receiver Information Receiver Power Splitter
(a) Time-switching receiver. (b) Power-splitting receiver.
Figure 1.5:SWIPT receivers.
networks was derived.
In [32], WPT with multi-carrier waveform was considered, where waveform optimiza- tion method was proposed.
2. SWIPT network, where energy and information are transferred simultaneously in the downlink by leveraging the property that RF signal carries both information and en- ergy. In [7], the authors first proposed a practical SWIPT system, where the receiver can obtain information and energy simultaneously from the received signal by using a time-switching or power-splitting method, as illustrated in Fig. 1.5.
For the time-switching-based SWIPT receiver, the RF antenna periodically switches be- tween an information receiver and an energy receiver for information detection and EH, respectively. In this way, the SWIPT receiver is able to detect information for a certain percentage of time, and harvest energy in the rest of the time. For the power-splitting- based SWIPT receiver, the received RF signal is first splitted into two streams by a pas- sive power splitter, and then one signal is sent to the information receiver and the other signal is sent to the energy receiver. Note that there are some other SWIPT architectures, such as the antenna-switching based SWIPT architecture, see [44].
The network with multiple randomly deployed SWIPT links was analyzed in [45] SWIPT for a multiple-input-single-output (MISO) broadcast channel was investigated in [46]. SWIPT in OFDM-based systems were further investigated in [47, 48]. Such systems are important, since 4G systems are based on OFDM. In [47], downlink OFDM-SWIPT in a multi-user system was studied, where the optimal resource allocation problem was solved. In [48], the resource allocation problem of an OFDM cellular system, which performs downlink SWIPT and uplink information transmission, was comprehensively studied.
Current studies on SWIPT often consider an ideal information transmission model (i.e., Gaussian signaling) and investigate the tradeoff between the information capacity and harvested energy [7, 49, 50]. In reality, SWIPT receivers are typically energy constrained
and may be incapable of performing high-complexity capacity-achieving coding/decod- ing scheme. Recently, SWIPT with practical coherent modulations was analyzed in [26]. Another commonly applied assumption in the SWIPT literature is that the average re- ceived signal power at the radio-frequency (RF) EH circuit is well above the RF-EH sen- sitivity level [7, 26, 49]. Hence, these studies ignore the impact of the RF-EH sensitivity level. In reality, practical state-of-the-art RF-EH circuits have power sensitivity require- ment in the range of−10dBm to−30dBm [2]. Guaranteeing a much higher received signal power than the RF-EH sensitivity level often requires an extremely short commu- nication range, which largely limits the application of SWIPT. Therefore, we consider a more general SWIPT system withM-ary modulation where the received signal power is not necessarily larger than the RF-EH sensitivity level. Since different constellation symbols may have different power levels, the amount of harvested energy may vary from symbol by symbol, and it is possible that some symbols can activate the RF-EH circuit but others cannot. Hence, it is important to accurately capture the effect of the RF-EH sensitivity level in analyzing the performance of SWIPT.
3. WPCN (wireless powered communication network), where energy is transferred in the downlink and information is transfer in the uplink [51]. In [27], the authors first pro- posed the WPCN network model. In this network, mobile users harvest RF energy emitted by a base station, and transmit information to the base station when it has har- vested enough energy. The WPCN is particularly useful in wireless sensor networks, since wireless sensors usually have very low downlink data rate but high uplink data rate, e.g., updating the sensed information to the sink. In [52], the authors further con- sidered a full-duplex WPCN, where an access point operating in a full-duplex manner, i.e., broadcasting wireless energy to a set of distributed users in the downlink and, and receiving independent information from the users via time-division multiple access in the uplink simultaneously.
However, this WPCN architecture suffers from a “doubly near-far" problem1: due to both the downlink and uplink distance dependent signal attenuation, where a far user from the access point, which receives less wireless energy than a nearer user in the downlink, has to transmit with more power in the downlink for reliable information transmission. To tackle the challenge of “doubly near-far" problem, the direct solution is the decoupling of the uplink and the downlink [53, 37], i.e., the energy emitter and information receiver should be separated. In [53], the authors proposed a novel WPCN consisting of a primary and a secondary network. The low-power mobiles in a secondary network, i.e., the secondary transmitters, harvest ambient RF energy from transmissions
by nearby active transmitters in a primary network, i.e., primary transmitters, while op- portunistically transit information to the secondary receivers by accessing the spectrum licensed to the primary network. In [37], the authors propose a cellular network consist- ing of base stations, mobile users and power beacons (PBs). Therefore, the users are able to harvest RF energy from the nearby PBs and transmit information to their associated base stations.