A Low-Complexity Bound Estimation Technique for Maximum Likelihood Receivers

In this paper, we develop a novel algorithm to compute the union bound for maximum likelihood (ML) receivers for multi-input multi-output systems in real-time applications. The proposed strategy can effectively reduce the complexity of the minimum Euclidean distance search (MEDS) for the union bound by employing sphere decoding algorithms (SDAs) with modified Schnorr-Euchner (SE) enumeration. Furthermore, due to the importance of the initial radius (IR) for the complexity reduction of SDAs, the IR can be obtained according to channel statistics. Simulations illustrate that the proposed algorithm achieves considerable complexity reduction, while maintaining the accuracy of MEDS and obtaining an acceptable union bound. In other words, the proposed algorithm can be considered as a performance indicator, which can be exploited in many wireless communication algorithms, e.g., power allocation algorithms for cellular communications, precoding for multi-user MIMO systems, and dynamic pilot allocation for MIMO systems. With the aid of the performance indicator, the communication systems can be more flexible for different scenarios in the sense that the performance can be improved in terms of spectral efficiency, capacity, symbol error rate (SER), etc.