Sparse code multiple access (SCMA) scheme is considered to be one promising non-orthogonal technology for the future fifth generation (5G) communications. Due sparse nature, message passing algorithm (MPA) has been used at receiver achieve close maximum likelihood (ML) detection performance with much lower complexity. However, complexity order of MPA still exponential size codebook and degree signal superposition on a given resource element. In this paper, we propose novel low iterative...

Sparse Bayesian learning (SBL) can be implemented with low complexity based on the approximate message passing (AMP) algorithm. However, it does not work well for a generic measurement matrix, which may cause AMP to diverge. Damped has been used SBL alleviate problem at cost of reducing convergence speed. In this work, we propose new algorithm structured variational inference, leveraging unitary transformation (UAMP). Both single vector and multiple problems are investigated. It is shown...

An alternative derivation for the well-known approximate message passing (AMP) algorithm proposed by Donoho is presented in this letter. Compared with original derivation, which exploits central limit theorem and Taylor expansion to simplify belief propagation (BP), our resorts expectation (EP) neglect of high-order terms large system limit. This leads a different yet provably equivalent form passing, explicitly establishes intrinsic connection between AMP EP, thereby offering some new...

In this letter, we consider the direction of arrival (DOA) estimation problem from one-bit quantized measurements in both single and multi snapshot scenarios. First, by formulating DOA as a generalized linear model inference problem, recently sparse Bayesian learning (Gr-SBL) algorithm is applied to solve it. Then, Gr-SBL extended scenario decoupling into sequence sub-problems. Numerical results demonstrate efficiency proposed algorithms.

In this letter, we present a unified Bayesian inference framework for generalized linear models (GLM) which iteratively reduces the GLM problem to sequence of standard model (SLM) problems. This provides new perspectives on some established algorithms derived from SLM ones and also suggests novel extensions other algorithms. Specific instances elucidated under such are versions approximate message passing (AMP), vector AMP (VAMP), sparse learning (SBL). It is proved that resultant version...

In this letter, we reveal that in the massive multiple-input multiple-output system with large bandwidth, sub-channels of orthogonal frequency division multiplexing share approximately sparse common support due to difference subcarriers. We use approximate message passing nearest neighbor sparsity pattern learning (AMP-NNSPL) algorithm adaptively learn underlying structure for improving accuracy channel estimation, where strategy is newly derived by solving an optimization problem. addition,...

This paper considers the generalized bilinear recovery problem, which aims to jointly recover vector b and matrix X from componentwise nonlinear measurements <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\text {Y}}\sim p({\text {Y}}|{\text {Z}})=\prod \limits _{i,j}p(Y_{ij}|Z_{ij})$ </tex-math></inline-formula> , where {Z}}={\text {A}}({\text {b}}){\text {X}}$ {A}}(\cdot)$ is a known affine linear...

In this paper, we propose an expectation propagation based iterative multi-user detection algorithm for multiple input output interleave-division access (MIMO-IDMA) systems with high-order modulation. The proposed detector can be well integrated into the traditional structure of turbo receivers MIMO-IDMA systems. By formulating a scalar factor graph representation and choosing Gaussian distribution as projection set symbol belief, overall complexity reduced to scaling linearly number users,...

In this letter, we propose an efficient structured approximate message passing (Str-AMP) detector for multi-user spatial modulation systems. Str-AMP consists of two steps in each iteration. First, a decoupling operation is performed the same way as AMP. Then, at denoising step, to exploit sparsity SM signals, computes element signals using not only its own statistics but also those neighboring elements belonging user. Since maintains scalar passing, it computationally efficient. Simulation...

To address the challenging problem of downlink channel estimation with low pilot overhead in massive multiple-input multiple-output (MIMO) systems, an empirical Bayesian block expectation propagation (EP) algorithm is proposed. Specifically, a Bernoulli-Gaussian prior model proposed to fit underlying sparsity, and EP derived estimate channels more accurately by clustering all taps that pertain same delay, while parameters are learned minimizing Bethe free energy. Simulation results show...

In this paper, an approximate message passing-based generalized sparse Bayesian learning (AMP-Gr-SBL) algorithm is proposed to reduce the computation complexity of Gr-SBL algorithm, meanwhile improving robustness GAMP against measurement matrix deviated from independent and identically distributed Gaussian for linear model (GLM). According expectation propagation, original GLM iteratively decoupled into two sub-modules: standard (SLM) module minimum mean-square-error module. For SLM module,...

Neural networks with binary weights are computation-efficient and hardware-friendly, but their training is challenging because it involves a discrete optimization problem. Surprisingly, ignoring the nature of problem using gradient-based methods, such as Straight-Through Estimator, still works well in practice. This raises question: there principled approaches which justify methods? In this paper, we propose an approach Bayesian learning rule. The rule, when applied to estimate Bernoulli...

Non-orthogonal multiple access (NOMA) on shared resources has been identified as a promising technology in 5G to improve resource efficiency and support massive all kinds of transmission modes. Power domain code NOMA have extensively studied evaluated both literatures 3GPP standardization, especially for the uplink where large number users would like send their messages base station. Though different transmitter side design, power share same need advanced multi-user detection (MUD) design at...

In this paper, we address the problem of recovering complex-valued signals from a set linear measurements. Approximate message passing (AMP) is one state-of-the-art algorithm to recover real-valued sparse signals. However, extension AMP case nontrivial and no detailed rigorous derivation has been explicitly presented. To fill gap, extend complex Bayesian approximate (CB-AMP) using expectation propagation (EP). This novel perspective leads concise CB-AMP without sophisticated transformations...

Due to limited volume, weight and power consumption, micro-satellite has reduce data transmission storage capacity by image compression when performs earth observation missions. However, the quality of images may be unsatisfied. This paper considers problem recovering sparse signals exploiting their unknown sparsity pattern. To model structured sparsity, prior correlation support is encoded imposing a transformed Gaussian process on spike slab probabilities. Then, an efficient approximate...

Non-orthogonal multiple access (NoMA) as an efficient way of radio resource sharing has been identified a promising technology in 5G to help improving system capacity, user connectivity, and service latency communications. This paper provides brief overview the progress NoMA transceiver study 3GPP, with special focus on design turbo-like iterative multi-user (MU) receivers. There are various types MU receivers depending combinations detectors interference cancellation (IC) schemes....

In future wireless networks, one fundamental challenge for massive machine-type communications (mMTC) lies in the reliable support of connectivity with low latency. Against this background, paper proposes a compressive sensing (CS)-based random access scheme mMTC by leveraging inherent sporadic traffic, where both active devices and their channels can be jointly estimated overhead. Specifically, we consider uplink adopt pseudo pilots, which are designed under framework CS theory. Meanwhile,...

We consider the problem of recovering clustered sparse signals with no prior knowledge sparsity pattern. Beyond simple sparsity, interest often exhibits an underlying pattern which, if leveraged, can improve reconstruction performance. However, is usually unknown a priori. Inspired by idea k-nearest neighbor (k-NN) algorithm, we propose efficient algorithm termed approximate message passing nearest learning (AMP-NNSPL), which learns adaptively. AMP-NNSPL specifies flexible spike and slab on...

We consider the problem of recovering an unknown signal from general nonlinear measurements obtained through a generalized linear model (GLM). Based on unitary transform approximate message passing (UAMP) and expectation propagation, based AMP (GUAMP) algorithm is proposed for measurement matrices, in particular highly correlated matrices. Experimental results quantized compressed sensing demonstrate that GUAMP significantly outperforms state-of-the-art Generalized (AMP) vector (GVAMP) under

Given its capability in efficient radio resource sharing, non-orthogonal multiple access (NOMA) has been identified as a promising technology 5G to improve the system capacity, user connectivity, and scheduling latency. A dozen of uplink NOMA schemes have proposed recently this paper considers design universal receiver suitable for all potential designs schemes. Firstly, general turbo-like iterative structure is introduced, under which, expectation propagation algorithm (EPA) detector with...

Sparse code multiple access (SCMA) scheme is considered to be one promising non-orthogonal technology for the future fifth generation (5G) communications. Due sparse nature, message passing algorithm (MPA) has been used as receiver achieve close maximum likelihood (ML) detection performance with much lower complexity. However, complexity order of MPA still exponential size codebook and degree signal superposition on a given resource element. In this paper, we propose novel low iterative...

One major concern of employing frequency-domain pulse shaping (FDPS) to reduce the peak-to-average power ratio single-carrier frequency-division multiple-access (SC-FDMA) signals is decrease system spectral efficiency due excess bandwidth wasted in existing band allocation schemes (BASs). To improve FDPS-based SC-FDMA systems, a novel BAS proposed, where edge subcarriers for each user are overlapped with those all its neighbors. However, spectrum overlapping incurs multiuser interference and...

In future wireless networks, one fundamental challenge for massive machine-type communications (mMTC) lies in the reliable support of connectivity with low latency. Against this background, paper proposes a compressive sensing (CS)-based random access scheme mMTC by leveraging inherent sporadic traffic, where both active devices and their channels can be jointly estimated overhead. Specifically, we consider uplink adopt pseudo pilots, which are designed under framework CS theory. Meanwhile,...