TRIS Transceiver: SWIPT Optimization

• TRIS transceivers are engineered metasurfaces that directly modulate transmitted electromagnetic waves for joint wireless information and power transfer.
• They employ programmable meta-atoms with voltage-tunable components to achieve dynamic beamforming, multi-stream separation, and resource allocation.
• Integrated with cooperative and cognitive networks, TRIS enhances network lifetime and spectral–energy efficiency through unified energy and data delivery.

A transmissive reconfigurable intelligent surface (TRIS) transceiver is a class of SWIPT (Simultaneous Wireless Information and Power Transfer) or joint WPT/WIT hardware that utilizes engineered metasurfaces to achieve spatial control over electromagnetic wave transmission, enabling adaptive wireless energy and information transfer via programmable physical layer transformations. Unlike conventional reflective RIS, the TRIS directly modulates transmission through (rather than reflection from) a metasurface interface, opening new modalities in SWIPT architectures, multihop relaying, and resource allocation.

1. Principles and Architecture of TRIS Transceivers

TRIS transceivers employ a controllable array of meta-atoms or unit cells engineered to modulate the phase, amplitude, and polarization of incident electromagnetic waves during transmission. The key function is to establish programmable channel transfer characteristics between transmitter and receiver, typically by means of voltage-tunable impedances or varactor diodes distributed across a planar surface. In SWIPT, TRIS is deployed to spatially focus information and energy-carrying beams dynamically, adapting to channel and user requirements (Krikidis et al., 2014).

The TRIS replaces conventional static passive transmission media between source and receiver, providing additional degrees of freedom for physical-layer resource optimization. Unlike reflective metasurfaces—wherein the scattered field is redirected—the TRIS transformation occurs during forward wave propagation, enabling simultaneous spatial beamforming for different target points, multi-stream separation, and joint energy/data delivery.

Block-level architecture typically consists of:

• Transmit source (BS/AP) with standard amplification
• TRIS module (planar or conformal), comprised of M×N meta-atoms, programmable via embedded CPUs or controllers
• Receive side (EH receiver, ID receiver, or hybrid SWIPT node)
• Optional feedback links for CSI acquisition and TRIS reconfiguration

In multi-user settings, TRIS can serve as a dense access point for distributed antenna systems, enabling joint transmission of information streams and power transfer to geographically separated receivers (Krikidis et al., 2014).

2. SWIPT Protocols and Receiver Models

TRIS transceiver deployment supports canonical SWIPT receiver models (Krikidis et al., 2014):

• Time-switching (TS): The receiver alternates between EH and ID over a block period.
• Power-splitting (PS): Incident RF is divided into fractions $\rho$ (ID) and $1-\rho$ (EH) instantaneously.
• Antenna-switching (AS): Spatial assignment of subset antennas for EH versus ID.
• Spatial-switching (SS): Eigen-channels (from SVD decomposition of the MIMO channel) are allocated for EH or ID; particularly natural for TRIS, which can manipulate transmission eigenmodes.

TRIS facilitates dynamic reallocation of resources according to these protocols, either at the hardware (direct spatial transform) or protocol layers (controller software). The fundamental rate-energy region $\mathcal{R}$ is defined by all pairs $(R,E)$ achievable under a given transmit power $P_t$ and splitting parameterization, e.g.:

$$R \leq \log_2\!\bigl(1 + \frac{(1-\rho)P_t|h|^2}{\sigma^2}\bigr),\qquad E \leq \eta\rho P_t|h|^2$$

with $h$ representing the overall channel, including TRIS-imposed transformations.

3. Resource Allocation and Optimization

TRIS systems necessitate joint optimization of:

• Surface element states (phase/amplitudes)
• Transmit power allocation
• Beamforming weights (for multi-antenna systems)
• Mode-switching parameters (TS, PS, AS, SS ratios)
• User scheduling

Standard frameworks for this are Lagrangian optimization and dual decomposition across physical resources (such as time, power, antenna/element allocation), often formulated as non-convex problems. When the underlying resource–rate/energy mappings are convex (e.g., PS+TS), global optima are obtained via convex solvers; otherwise, heuristics such as greedy assignment or alternating maximization are employed (Krikidis et al., 2014).

For example, for PS+AS+TS joint allocation:

$$\max_{\tau, \rho, \{m,p_i\}} \; w_R R(\tau, \rho, m, \{p_i\}) + w_E E(\tau, \rho, m, \{p_i\})$$

subject to

$$0 \leq \tau \leq 1,\; 0 \leq \rho \leq 1; \;\sum_i p_i \leq P_t;\; m \in \{0,1,\dots,N_T\}; \; R \geq R_{min};\; E \geq E_{min}$$

where the TRIS transforms directly affect the effective channel gains in all terms.

Dual decomposition results in tractable subproblem optimizations (e.g., split the multidimensional resource allocation problem into independent time and power allocation routines).

TRIS systems additionally enable cooperative relaying and cognitive information-energy co-design; for instance, opportunistic harvesting from interference in multi-cell configurations or relay-based SWIPT with surface-controlled path selection (Krikidis et al., 2014).

4. Hardware Realization of TRIS

A typical TRIS comprises:

• Antenna subsystem: Planar or conformal meta-atom array, each cell often realized by microstrip patch or leaky-wave element, sometimes with varactor-based tuning.
• Matching network: For impedance coupling across a wide band, optimized to minimize insertion loss.
• Nonlinear rectifier circuit: For EH functionality, commonly Schottky diode-based with a load $R_{DC}$, described by the Shockley equation for current-voltage relation.
• Controller/driver layer: Embedded logic to update element states for spatial transform.

Efficiency is governed by RF–DC conversion characteristics:

$\eta_{RC}(P_{RF}, R_{DC}) = \frac{P_{DC}}{P_{RF}}$

with nonlinear dependence on RF input power and load. Typical rectifier output at moderate $P_{RF}$ follows:

$$V_{DC} \approx n V_T \ln\!\bigl(P_{RF}/P_{th}\bigr)$$

where $n$ is the diode ideality factor, $V_T$ the thermal voltage, and $P_{th}$ the turn-on threshold.

Design trade-offs include the selection of meta-atom element size/configuration, control granularity, load matching, and the minimization of switching and forward-drop losses. For advanced spatial switching, SVD-based allocation is supported by hardware capable of fine-grained phase control.

5. Integration with Multihop, Cooperative, and Cognitive Networks

TRIS transceivers play a central role in emerging cooperative, cognitive, and relay-based SWIPT architectures (Krikidis et al., 2014):

• Cognitive SWIPT: Secondary transceivers use harvested RF energy from primary transmission to relay or transmit own data; optimization is jointly performed over beamforming and splitting ratios to maximize secondary user rate while ensuring primary QoS.
• Cooperative relaying: Selection and activation of relay nodes are controlled by TRIS-imposed spatial energy redistribution; power-split constraints and channel states determine optimal relay scheduling.
• Interference management: TRIS surfaces can spatially concentrate transmission to EH-only users, converting interference liabilities into energy assets via programmable energy accumulation and focused transmission.

6. Performance, Trade-offs, and Challenges

Metric studies demonstrate (Krikidis et al., 2014):

• PS outperforms AS by roughly 2.5 dB at high $P_t$.
• Greedy selection for antenna switching yields significant diversity gain over uniform assignment.
• TS lags due to inherent time-division losses.
• Multihop and multi-cell scenarios benefit most from TRIS-enabled resource adaptation.

Key benefits:

• Extended network lifetime via self-powered SWIPT nodes
• Unified energy and information flow design enables spectral–energy efficiency gains
• New resource dimensions in time, space, and frequency offered by TRIS programmability

Challenges:

• Nonlinear and load-dependent RF–DC conversion induces non-convexity in optimization
• Real-time CSI acquisition is needed for dynamic spatial switching and resource control
• Hardware limitations: PS circuits and fast surface switching create non-negligible insertion losses
• Security: Strong energy-focused beams may be susceptible to side-channel vulnerabilities and false CSI reporting by EH-only nodes

7. Future Directions and Extensions

TRIS transceivers underpin the broader development of programmable wireless environments, interfacing SWIPT, IRS (Intelligent Reflecting Surfaces), and fluid-antenna systems. The natural extension involves integrating TRIS with distributed massive MIMO, IRS, and multi-hop backbone design for 6G networks. Advanced algorithms for jointly optimized waveforms, spatial configuration, and meta-atom state schedules are required to fully exploit TRIS capabilities. Security, privacy, and hardware miniaturization remain important open research avenues (Krikidis et al., 2014).

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References:

• Simultaneous Wireless Information and Power Transfer in Modern Communication Systems (Krikidis et al., 2014)