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The paper presents a maximum likelihood symbol detection scheme with the assistance of a two-stage-ranking mechanism for massive MIMO systems. The proposed scheme first computes the QR decomposition to the channel matrix in order to obtain them corresponding unitary and upper triangular matrices. Next, the ML mechanism is conducted to recursively estimate the transmitted symbols layer by layer. In...
This paper studies the sparse recovery problem. Of particular interest is the well known approximate message passing (AMP) algorithm. AMP enjoys low computational complexity and good performance guarantees. However, the algorithm and performance analysis heavily rely on the assumption that the measurement matrix is a standard Gaussian random matrix. The main contribution of this paper is an improved...
In this paper, we present a multistage group-decision-aid MUD (MG-MUD) for the uplink multirate code division multiple access (CDMA) systems. To provide good tradeoff between the performance and computational complexity, the new MUD is based on the widely MMSE criterion and constructed by a bank of group detectors in each stage. First, the users are classified into different groups according to their...
This letter presents an effective space-time multiuser detector (MUD) with the assistance of soft information in multipath code division multiple access (CDMA) channels. The space-time MUD considered is a simple, separable spatial-temporal filter which consists of a single spatial filter and a single temporal filter. Based on the soft-decision outputs determined in the previous iteration, the soft...
This paper addresses a low complexity multi-rate multiuser detector (MUD) for the uplink multi-carrier code division multiple access (MC-CDMA) systems. The new MUD is an iterative groupwise receiver with the assistance of soft information to refine the interference estimates to enhance the interference cancellation capability. The users are first classified into different groups according to their...
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