Simultaneous Wireless Info & Power Transfer

• SWIPT is a communication framework that uses RF signals for simultaneous information transfer and energy harvesting, key for batteryless and IoT devices.
• Advanced receiver models such as power-splitting, time-switching, and antenna-switching enable flexible tradeoffs between data decoding and energy capture.
• Optimized resource allocation and beamforming techniques ensure that system designs meet stringent energy and rate requirements in multi-user and relay scenarios.

Simultaneous Wireless Information and Power Transfer (SWIPT) System

Simultaneous Wireless Information and Power Transfer (SWIPT) refers to an integrated communication paradigm in which radio frequency (RF) signals are used to deliver both energy (for energy harvesting, EH) and information (for information decoding, ID) over the same wireless medium. SWIPT is motivated by the requirements of future wireless networks—including IoT, self-powered sensors, and relays—where energy-limited or batteryless devices must sustain operation without compromising data-transfer capabilities. SWIPT system design encompasses circuit-level architectures, transmission strategies, resource allocation, and cross-layer optimization, with hardware and information-theoretic constraints shaping system performance and deployment (Krikidis et al., 2014, Wei et al., 2021).

1. System Architectures and Receiver Models

SWIPT systems are classified according to the RF-to-information/energy conversion stage, available CSI, and transmission topology. Key receiver architectures include:

• Time-Switching (TS): The receiver alternates between ID and EH over disjoint timeslots. Symbol interval T is divided as τT for EH, (1–τ)T for ID, with 0 ≤ τ ≤ 1. This approach is hardware-simple but achieves only exclusive operation per slot (Krikidis et al., 2014).
• Power-Splitting (PS): The receiver employs a power splitter, dividing the incoming RF signal into two streams: α fraction to EH and 1–α to ID (0 ≤ α ≤ 1). PS enables truly simultaneous ID and EH at the RF front-end, but introduces challenges in hardware matching and splitting loss (Krikidis et al., 2014, DI et al., 2014). An important hardware realization is the diplexer-based receiver, which separates baseband and doubling-frequency components, with each capturing half the received power (fixed ratio α = 0.5) (Qin et al., 2016).
• Antenna-Switching (AS): On a multi-antenna receiver, a subset of antennas is dynamically switched to EH or ID in each time interval (Krikidis et al., 2014). Spatial and eigenmode switching variants exist for MIMO systems.
• Integrated Receivers: Emerging architectures such as IntRx directly rectify all received RF energy and extract information after rectification, removing the need for mixers or oscillators and exploiting the nonlinear characteristics of rectifiers (Kim et al., 2021).

At the transmitter, SWIPT may rely on:

• Transmitter-centric (energy beamforming): Joint spatial/temporal precoding to focus energy and control interference (Xu et al., 2013, Wei et al., 2021).
• Receiver-centric (passive splitting): Standard waveforms, with adaptive receiver-side resource splits, dominate in cost- or complexity-constrained deployments (Krikidis et al., 2014).

2. Mathematical Foundations and Channel Models

A canonical SWIPT SISO system is modeled as:

$y = h\sqrt{P_t}x + n$

where $x$ is the unit-power symbol, $h$ the channel coefficient, $P_t$ the transmit power, and $n$ AWGN. The received RF power is $P_r = P_t|h|^2$.

After splitting:

• ID SNR: $\mathrm{SNR} = \frac{(1-\alpha)P_r}{\sigma^2}$
• EH Power: $P_{EH} = \eta \alpha P_r$, with 0 < η≤1 as the RF/DC conversion efficiency.

For PS, the achievable rate and EH formulations are (DI et al., 2014, Krikidis et al., 2014):

$$R(\alpha) = \log_2\left(1 + \frac{(1-\alpha)P_t|h|^2}{\sigma^2}\right)$$

$E(\alpha) = \eta\,\alpha\,P_t|h|^2 T$

Multi-user/multi-antenna SWIPT leverages channel vectors and matrices, with beamforming and spatial splitting adding further complexity (Xu et al., 2013, Zhang et al., 23 Oct 2025, Luo et al., 12 Sep 2025). Realistic relay/DF-AF multihop systems layer these models to account for harvested power at relays and multi-stage information bottlenecks (DI et al., 2014, Liu, 2016, Asiedu et al., 2019).

For practical circuits, nonlinearities in EH are often captured using logistic (sigmoid) or circuit-based diode models (Wei et al., 2021, Luo et al., 12 Sep 2025).

3. Optimization and Resource Allocation Frameworks

Resource allocation in SWIPT targets maximizing weighted rate–energy tradeoffs under transmit power, rate, and harvested power constraints. In single-user links, one solves:

$$\max_{P, \alpha}\ R(\alpha),\quad \text{s.t. } E(\alpha) \geq E_{\min},\ 0 \leq \alpha \leq 1$$

With channel state information at the transmitter (CSIT), joint optimization over transmit power and splitting achieves superior R–E performance via Lagrangian dual methods, water-filling for adaptive power control, and closed-form KKT solutions for optimal splitting (Hu et al., 2014).

In multiuser (MISO/MIMO) settings, optimization typically involves semidefinite relaxation (SDR) of rank-constrained beamforming problems:

$$\begin{aligned} &\max_{\{w_i\}, \{v_j\}, \{\alpha_k\}}\ \sum_{i} R_i \ &\text{subject to } P_{EH,j} \geq Q_j^{\min},\ P_{\text{tot}} \leq P_{\max} \end{aligned}$$

where $w_i$ are information beams and $v_j$ energy beams. Rank-one optimality often holds, so optimal solutions correspond to actual beamformers (Xu et al., 2013, Luo et al., 12 Sep 2025).

Multi-hop relay systems require joint optimization of PS ratios, subcarrier pairing, and source/relay power using separation principles (pairing → splitting → power allocation) for tractability (DI et al., 2014, Liu, 2016).

For emerging architectures (e.g., fluid-antenna, pinching-antenna, near-field), the resource allocation is extended to include joint optimization over spatial parameters—antenna positions—often via alternating optimization (AO) and Taylor expansion surrogates for convexification (Zhang et al., 23 Oct 2025, Zhou et al., 16 Jul 2024, Li et al., 26 Apr 2025, Zhang et al., 2023).

4. Applications and Key System Variants

Relay and cooperative systems: SWIPT relaying extends two-hop to multi-hop networks where all relays harvest energy from received signals and forward accordingly. In OFDM relaying, joint subcarrier pairing, splitting, and power allocation lead to significant sum-rate gains. The optimal relay position for SWIPT moves closer to the source—contrasting with the mid-point ideal in conventional relaying—since harvested energy is maximized nearer the energy source (DI et al., 2014, DI et al., 2015, Liu, 2016, Asiedu et al., 2019).

Multi-user and interference channels: In MISO BC scenarios, optimal beamforming protocols depend on interference cancellation capability of ID receivers and the location-based allocation of EH vs. ID roles (Xu et al., 2013). In multi-transmitter interference channels, collaborative energy beamforming and signal splitting enable distributed transmitters to service both EH and ID with significant R–E region enlargement over no-/partial-cooperation baselines (Lee et al., 2014).

Fluid and pinching-antenna architectures: Spatially reconfigurable antennas (fluid antennas, pinching antennas) enable dynamic shaping of the propagation environment, allowing near-optimal steering of both energy and information signals. AO-based algorithms jointly optimize antenna positions and resource allocation, outperforming fixed-position systems and yielding up to 50% boosts in harvested energy and significant rate gains (Zhang et al., 23 Oct 2025, Zhou et al., 16 Jul 2024, Li et al., 26 Apr 2025).

Near-field SWIPT and hybrid arrays: In the electromagnetic near-field, spherical-wave propagation enables simultaneous focusing of energy and information to multiple locations. Hybrid analog–digital array designs using semidefinite relaxation and penalty-based AO achieve near-optimal efficiency, and it is shown that (contrary to far-field) no dedicated energy beam is needed, as a single near-field beam can satisfy both energy and SINR constraints at multiple users (Zhang et al., 2023).

Optical and integrated receiver SWIPT: Resonant-beam optical SWIPT achieves multi-watt DC charging and multi-bps/Hz rates over tens of meters, with the rate–energy tradeoff controlled via beam splitting (Bai et al., 2021, Fang et al., 2021). Integrated receivers employing pulse-position modulation exploit nonlinear rectifier characteristics to decode information from rectified DC signals, enabling energy- and computation-constrained IoT devices to operate with minimal hardware (Kim et al., 2021).

5. Implementation and Design Insights

• Power splitting is fundamental: Optimal SWIPT often requires adaptive PS with α tuned to channel realization, energy demand, and circuit nonlinearity (DI et al., 2014, DI et al., 2015, Liu, 2016).
• Dedicated energy beams are not always necessary: In MIMO/MISO settings, type-I ID receivers need no energy beams; null-space beamforming under Gaussian signaling suffices. Dedicated beams become useful only for receivers with energy-centric waveforms operating in high-efficiency EH regimes, at the cost of additional complexity (Luo et al., 12 Sep 2025, Xu et al., 2013, Zhang et al., 2023).
• Relay placement differs from conventional wisdom: For SWIPT, DF relays yield maximal rate when deployed nearer the source to maximize harvested RF power; otherwise, the system is EH-bottlenecked (DI et al., 2014, DI et al., 2015).
• Hardware nonlinearity critical for architecture and waveform design: Nonlinear circuit responses imply high-PAPR and deterministic waveforms can yield superior energy transfer, but favor simpler Gaussian signaling for moderate-to-low input RF powers (Kim et al., 2021, Luo et al., 12 Sep 2025).
• System-level performance factors: The trade-off between information rate and harvested energy is sensitive to the choice of parameters (PS/TS fraction, power budget, CSI quality), network topology, and hardware design. System optimization is generally tractable via SDP/convex relaxations, alternating optimization, and fractional programming. In multi-hop and relay networks, closed-form expressions for optimal splitting exist and enable scalable deployment (DI et al., 2014, Asiedu et al., 2019).

6. Trends, Extensions, and Open Technical Challenges

SWIPT continues to develop along multiple research trajectories:

• Nonlinear and physically-accurate EH models: Incorporating saturation and circuit-level equations yields more robust and performant allocation.
• Reconfigurable antenna and metasurface integration: Leveraging RIS and dynamic antenna positioning unlocks new performance gains and spatial flexibility (Zhang et al., 23 Oct 2025, Zhou et al., 16 Jul 2024).
• Near-field and massive-MIMO SWIPT: Spherical-wave focusing and null-space designs allow millimeter-wave and THz SWIPT for ultra-dense IoT deployments (Zhang et al., 2023).
• Machine learning and large-scale network optimization: Training models for channel prediction, EH circuit mapping, or distributed allocation is a current research topic (Wei et al., 2021).
• Imperfect CSI and practical protocol design: Robust and outage-constrained resource allocation and near-optimal time-frequency split computation remain active, especially for TDD/FDD systems where CSI must be balanced against energy and data needs (Liu et al., 2016).
• Hybrid RF/optical SWIPT: The use of optical beamforming for high-power, long-range SWIPT brings new degrees of design freedom and introduces optical circuit constraints (Bai et al., 2021, Fang et al., 2021).

Open challenges include circuit-aware joint waveform/beamforming optimization, robust multi-user design under practical CSI acquisition and non-ideal hardware, and large-scale network deployment with dynamic topology.

7. Summary Table: SWIPT Architectural Approaches

Receiver Architecture	Simultaneity	Complexity	Typical Usage/Insights
Power-Splitting (PS)	Simultaneous	Moderate	General (DF relay, MISO, multi-hop)
Time-Switching (TS)	Alternating	Low	Simple IoT, low-rate, low-complexity
Diplexer-based	Simultaneous	Moderate	Fixed 50% split (RF hardware)
Integrated Reception	Simultaneous	Low	Ultra-low-power, PPM modulation
Antenna/Spatial Switch	Simultaneous	High	MIMO, multi-path splitting
Fluid/Pinching Antenna	Simultaneous	High	Position-optimized SWIPT
Hybrid Near-field	Simultaneous	High	Spherical-wave, analog/digital mix

This table summarizes the main receiver-side SWIPT architectures and their system-level roles as found in current literature (Krikidis et al., 2014, Xu et al., 2013, Zhang et al., 23 Oct 2025, Qin et al., 2016, Kim et al., 2021, Zhang et al., 2023).

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In conclusion, SWIPT is a rigorously-developed framework for combining RF-based power delivery and data communication. Its theoretical foundation is now mature, but new directions—such as fluid antennas, near-field propagation, nonlinear harvesting, and optical links—continue to expand SWIPT toward more versatile, efficient, and deployment-ready wireless networks (Krikidis et al., 2014, Wei et al., 2021, DI et al., 2014, Zhang et al., 23 Oct 2025, Zhang et al., 2023).