Indoor depth coverage is the key point of the LTE network quality which badly influences customer perception. However

accurate identification of the important weak-coverage indoor cells is always the difficulty of the following renovation works. Traditional optimization based on customer complaint and much on-site testing always takes long period and is also imprecise and expensive. To solve the above problems

we propose an identification and assessment method for indoor weak-coverage cells based on big data like FAST

MR

TA data. Practical applications prove that the proposed method works well on upgrading the coverage quality and user perception.