Joint Access Point Selection and Beamforming Design for Bistatic Backscatter Communication

Future Internet-of-Things networks are envisioned to use small and cheap sensor nodes with extremely low power consumption to avoid the extensive use of batteries. To provide connectivity to a massive number of these nodes, backscatter communication (BC) is emerging as an energy- and cost-efficient technology exploiting the reflection of radio frequency signals. However, challenges such as round-trip path loss and direct link interference (DLI) between the carrier emitter and the reader limit its performance. To tackle these limitations, this paper proposes a joint access point role selection and a novel beamforming technique for bistatic BC in a distributed multiple-input multiple-output setup. The proposed approach boosts the received backscattered energy while effectively mitigating DLI, thereby reducing the error probability. We also propose a channel estimation method tailored to operate under DLI conditions and propose a mismatch detector using estimated channel coefficients. Furthermore, we derive a closed-form expression for the probability of error for the detectors and model the quantization noise caused by DLI. Finally, comprehensive simulation results show that the proposed method with 1-bit analog-to-digital converters (ADCs) effectively mitigates DLI, reduces the quantization noise, and enhances backscattered signal energy, achieving performance comparable to the benchmark scenario with 8-bit ADCs.

💡 Research Summary

This paper addresses two fundamental challenges that limit the performance of bistatic backscatter communication (BiBC) for massive low‑power Internet‑of‑Things (IoT) deployments: the severe round‑trip path loss inherent to the cascade channel and the strong direct‑link interference (DLI) generated by the carrier emitter (CE) at the reader. The authors propose a joint access‑point (AP) role selection and transmit beamforming (BF) framework within a distributed multiple‑input multiple‑output (MIMO) architecture, where a set of spatially distributed APs can dynamically assume the role of either a CE or a reader. By judiciously assigning APs to these roles, the round‑trip distance between the CE, the backscatter device (BD), and the reader is minimized, yielding macro‑diversity gains that reduce path loss.

The core technical contributions are as follows. First, a three‑step maximum‑likelihood (ML) channel estimation algorithm is devised that works under DLI conditions. A reference AP equipped with high‑resolution analog‑to‑digital converters (ADCs) and full‑duplex capability first estimates its own BD‑AP channel (h_ref) from the backscattered pilot. Using this estimate, the cascade channels between the BD and all other APs are recovered, and finally h_ref is refined by exploiting all received pilot observations. The algorithm accommodates binary Hadamard pilots, which are well‑suited for low‑resolution digital‑to‑analog converters.

Second, the paper derives optimal detectors for both perfect channel state information (CSI) and imperfect CSI (including estimation errors). Closed‑form expressions for the symbol error probability are obtained, and a Gaussian approximation is used to model the quantization noise introduced by DLI when low‑bit ADCs are employed.

Third, the authors formulate a mixed‑integer nonlinear programming problem that simultaneously (i) maximizes the received backscattered signal power at the reader, (ii) enforces per‑antenna DLI constraints, and (iii) selects which APs act as CE or reader. The problem is solved with a low‑complexity greedy AP‑selection combined with a semidefinite‑programming (SDP) based BF design. This joint optimization yields a beam that focuses energy on the BD while keeping the DLI below a prescribed threshold, thereby allowing the use of coarse‑resolution (1‑bit) ADCs without sacrificing detection performance.

Extensive Monte‑Carlo simulations evaluate the proposed scheme under varying numbers of APs, antenna configurations, distances, and ADC resolutions (1, 4, and 8 bits). Compared with baseline methods that either ignore DLI or use only conventional BF, the proposed approach achieves a 5–10 dB improvement in effective SNR, a 3–6 dB increase in backscattered signal power, and bit‑error‑rate (BER) performance with 1‑bit ADCs that is comparable to the benchmark with 8‑bit ADCs. Complexity analysis shows that the algorithm scales linearly with the number of APs and quadratically with the antenna count, making real‑time implementation feasible.

In summary, the paper demonstrates that jointly optimizing AP role selection and transmit beamforming can simultaneously mitigate DLI and enhance backscatter energy, enabling ultra‑low‑resolution ADCs in distributed BiBC systems. This contribution bridges the gap between energy‑efficient IoT connectivity and practical hardware constraints, and opens avenues for future work on multi‑BD extensions, dynamic AP reconfiguration, and hardware prototyping.