  Intelligent reflecting surface (IRS) has emerged as a promising technique to
extend the wireless signal coverage of access point (AP) and improve the
communication performance cost-effectively. In order to reduce the path-loss of
the cascaded user-IRS-AP channels, the IRS-integrated AP architecture has been
proposed to deploy the IRSs and the antenna array of the AP within the same
antenna radome. To reduce the pilot overhead for estimating all IRS-involved
channels, in this paper, we propose a novel codebook-based IRS reflection
design for the IRS-integrated AP to enhance the coverage performance in a given
area. In particular, the codebook consisting of a small number of codewords is
designed offline by employing an efficient sector division strategy based on
the azimuth angle. To ensure the performance of each sector, we optimize its
corresponding codeword for IRS reflection pattern to maximize the
sector-min-average-effective-channel-power (SMAECP) by applying the alternating
optimization (AO) and semidefinite relaxation (SDR) methods. With the designed
codebook, the AP performs the IRS reflection training by sequentially applying
all codewords and selects the one achieving the best communication performance
for data transmission. Numerical results show that our proposed codebook design
can enhance the average channel power of the whole coverage area, as compared
to the system without IRS. Moreover, our proposed codebook-based IRS reflection
design is shown to achieve significant performance gain over other benchmark
schemes in both single-user and multi-user transmissions.
