Intelligent reflecting surface-aided network planning

Intelligent reflecting surface (IRS) composed of a large number of low-cost, phase-adjustable passive reflecting elements, which is an attractive solution of overcoming the signal attenuation and interference. IRS can be used as a low-power passive system with signal enhancement and interference suppression. However, the planning problem of a large-scale network contains a great numbers of base stations (BSs) and IRSs is challenging. The network planning problem considers limited deployment cost and signal enhancement at the same time is vital. Here, the 6G wireless signal coverage (WSC) problem with the consideration of both BS and IRS is considered. More specifically, the 6G WSC problem is first formulated through the integer linear programming. Due to its obvious NP-hardness, two efficient heuristic algorithms that can reach a near-optimal solution, that is, the WSC algorithm and the tree-based WSC (TBWSC) algorithm is then proposed. Simulation-based results showed that the proposed WSC algorithm achieves lower total cost than that of the TBWSC algorithm but also results in lower signal quality. The proposed TBWSC algorithm obtains the planning result with the highest signal quality and slightly higher total cost. Both proposed algorithms can find better planning results of multiple BSs and IRSs for 6G wireless communications.