Pilot design method for large-scale MIMO system

Abstract

The invention relates to a wireless communication technology, in particular to a pilot design method for a large-scale MIMO system. The method comprises the following steps of randomly generating a first pilot sequence group by adopting real value coding, and taking two individuals with the largest fitness values in the group as a first parent and a second parent; carrying out crossover and mutation operation on the first parent and the second parent to acquire a third filial generation and a fourth filial generation, and storing the third filial generation and the fourth filial generation into a second pilot sequence group; storing a plurality of individuals with the larger fitness values of the second pilot sequence group into a third pilot sequence group; and selecting an optimal individual and an individual with the largest fitness value in the third pilot sequence group, and if the fitness value of the optimal individual in the third pilot sequence population is equal to the fitness value of the optimal individual of the first pilot sequence for many times, acquiring an optimal pilot position sequence. According to the method, a genetic model is built, and meanwhile, inner andouter circulation mechanisms are introduced to ensure the acquisition of the optimal individual in the population, so that the accuracy of channel estimation is improved while the pilot overhead is reduced.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a pilot design method of a massive MIMO system. Background technique [0002] The basic feature of a massive MIMO system is to equip dozens or even hundreds of antennas on the base station side, which is an order of magnitude more than the traditional MIMO system. The base station uses a large number of antennas to serve multiple users simultaneously in the same time-frequency resource. Compared with traditional MIMO, massive MIMO has many advantages: higher data rate; higher power efficiency and spectrum efficiency; better link reliability; relatively cheap, low-power devices can be used, etc. Massive MIMO technology is one of the most potential research directions for green broadband wireless communication in the future. Accurate channel state information (Channel State Information, CSI) acquisition plays a particularly important role in downlink channel beam m...

AI Technical Summary

Problems solved by technology

[0004] At present, there are not many algorithms for pilot optimization based on compressed sensing massive MIMO channel estimation. Many researches focus on the improvement of sparse signal reconstruction algorithms, and do not consider how to design the best fixed pilot pattern to make channel estimation improved performance

Images