WiFi-based contactless sensing has found numerous applications in the fields of smart home and health care owning to its low-cost, non-intrusive and privacy-preserving characteristics. While promising in many aspects, the limited sensing range and interference issues still exist, hindering the adoption of WiFi sensing in real world. In this paper, inspired by the SNR (signal-to-noise ratio) metric in communication theory, we propose a new metric named SSNR (sensing-signal-to-noiseratio) to quantify the sensing capability of WiFi systems. We theoretically model the effect of transmitter-receiver distance on sensing coverage. We show that in LoS scenario, the sensing coverage area increases first from a small oval to a maximal one and then decreases. When the transmitter-receiver distance further increases, the coverage area is separated into two ovals located around the two transceivers respectively. We demonstrate that, instead of applying complex signal processing scheme or advanced hardware, by just properly placing the transmitter and receiver, the two well-known issues in WiFi sensing (i.e., small range and severe interference) can be greatly mitigated. Specifically, by properly placing the transmitter and receiver, the coverage of human walking sensing can be expanded by around 200%. By increasing the transmitter-receiver distance, a target's fine-grained respiration can still be accurately sensed with one interferer sitting just 0.5 m away. CCS Concepts: • Human-centered computing → Ubiquitous and mobile computing systems and tools; Ubiquitous computing; Mobile computing; Ambient intelligence.