Mapping Rule And Detector In Massive GSSK-MIMO System

With the development of the information age, people have become more and more demanding towards the quality of service of communication. The symbol rate of MIMO system can no longer satisfy people’s needs. As a result, massive-MIMO technology is introduced. Although massive-MIMO system enhances reliability and increases data rate, the larger scale of antenna creates new problems. The transmitter side has problems of power distribution, too large number of RF chains and so on. In the receiving end, it will increase the complexity and energy consumption of the signal processing. It also increases the complexity of hardware circuit.Generalized Space Shift Keying (GSSK) modulation avoids the restriction of having only one active transmit-antenna in each time-slot, and allows multiple antennas to be simultaneously active. The phase and amplitude of the signaling do not carry information, using only antenna indices to relay information instead. In so doing, it can reduce the inter-channel interference (ICI). Also, it doesn’t require excessive RF chains. In the receiving end, we only need to detect which antenna is activated, thereby reducing the complexity and energy consumption of the signal processing. It also reduces the complexity of hardware circuit.Since GSSK modulation can overcome some disadvantages of massive-MIMO system, this study aims to research the mapping rule and detection for massive GSSK-MIMO system.Firstly, this study introduces the mapping rule of GSSK generated from co-lexicographic order. It can be done for GSSK mapping and demapping through calculation, overcoming the disadvantage of listing method taking too much memory in the massive GSSK-MIMO system. In addition, due to the large size of the antenna, the existing data type of computer can’t store data efficiently. This paper applies a method of adding, subtracting, multiplying, dividing and combination calculation of large numbers to solve the problem.Secondly, in the research of detection at the receiving end, the subspace pursuit (SP) algorithm is introduced to be applied to this system. As a result, compared with algorithm of ZF, NCS and so on, the algorithm of SP owns lower bit error rate (BER) and complexity.Thirdly, an algorithm based on the Lagrange multipliers is applied in this study. In the massive MIMO system, there is a relatively lower complexity of LAS. The Lagrange multiplier is introduced to improve the algorithm, which is called LAS with Lagrange multiplier (LLAS). The simulation result shows that LLAS algorithm has a lower bit error rate (BER).