Design of Adaptively Scaled Belief in Multi-Dimensional Signal Detection for Higher-Order Modulation

Takahashi, Takumi; Ibi, Shinsuke; Sampei, Seiichi

doi:10.1109/tcomm.2018.2883307

Cited by 38 publications

(41 citation statements)

References 32 publications

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“…The proposed SMBP detector can be extended to QAM signaling after some appropriate mathematical manipulations proposed in [9].…”

Section: A Initial Detectionmentioning

confidence: 99%

“…where φ n,m is the effective noise, and the variance is derived from the expectation of random variables z n andx m as (9) and (10) under the SGA condition, the conditional PDF of r n,m can be expressed as…”

Section: A Initial Detectionmentioning

confidence: 99%

“…. ,r N,m are (conditional 2 ) independent under the SGA condition in (9), l m can be approximated by…”

Section: A Initial Detectionmentioning

confidence: 99%

“…The BP-based signal detector can take advantage of the law of large numbers to simplify the computation of conditional symbol expectation. The most noticed BP-based detector is approximate message passing (AMP) [10], [11], which is systematically derived from an exact approximation of Gaussian BP (GaBP) [8], [9] in the large-system limit occurring when the input and output dimensions, M and N respectively, increase to infinity for a given compression rate ρ = N/M. These algorithms consist of only scalar-wise operations, and therefore can achieve the computational complexity O(M N) for each iteration process.…”

Section: Introductionmentioning

confidence: 99%

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Subspace Marginalized Belief Propagation for mmWave Overloaded MIMO Signal Detection

Takahashi

Ibi

Tölli

et al. 2020

ICC 2020 - 2020 IEEE International Conference on Communications (ICC)

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This paper deals with mmWave overloaded multiuser multi-input multi-output (MU-MIMO) detection, where the number of receive antennas is less than that of transmitted streams. Belief propagation (BP) is well known strategy for achieving large-scale MU detection (MUD) with low-complexity and high-accuracy. However, in mmWave massive MUD, the BPbased signal detector is subject to ill convergence behavior of iterative detection due to under-determined problem induced by spatial overloading and strong correlation among user channels induced by narrow angular spread of receive signal and lineof-sight (LOS) environments. To alleviate these impairments, we propose a novel iterative MUD approach based on beam-domain subspace marginalized BP (SMBP). Exploiting the approximate sparsity of beam-domain channels, the maximum likelihood (ML) principle is used to combine the strongly correlated signal subspace with reduced dimension while the BP-based detection is used for the remaining complementary subspace. The space partitioning criterion is adaptively determined based on channel state information (CSI) so that the two subspaces are as orthogonal as possible. Numerical results show that the proposed method is able to serve a massive number of wireless connections with low computational complexity even in the LOS environment, while providing excellent BER performance.

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“…The proposed SMBP detector can be extended to QAM signaling after some appropriate mathematical manipulations proposed in [9].…”

Section: A Initial Detectionmentioning

confidence: 99%

Section: A Initial Detectionmentioning

confidence: 99%

“…. ,r N,m are (conditional 2 ) independent under the SGA condition in (9), l m can be approximated by…”

Section: A Initial Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Subspace Marginalized Belief Propagation for mmWave Overloaded MIMO Signal Detection

Takahashi

Ibi

Tölli

et al. 2020

ICC 2020 - 2020 IEEE International Conference on Communications (ICC)

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“…The layered BP proposed in this paper can be extended to QAM signaling after some appropriate mathematical manipulations[15] …”

mentioning

confidence: 99%

Concatenated Beam- and Antenna-domain Layered Belief Propagation for Large MIMO Detection

Takahashi

Tölli

Ibi

et al. 2019

2019 16th International Symposium on Wireless Communication Systems (ISWCS)

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This paper proposes concatenated beam-and antenna-domain belief propagation (BP) based signal detector for realizing low-complexity large multiuser multi-input multioutput (MU-MIMO) detection. As a low-complexity strategy for large-scale MU detection (MUD), group-specific signal detection in the beam domain has been proposed, where user equipments (UEs) are grouped based on the long-term channel statistics at a base station (BS) to design outer beamformer (OBF). In this case, the BP-based algorithm is effective as the subsequent signal detector to compensate for the performance degradation due to the dimensionality reduction caused by the OBF. However, the convergence characteristics of beam-domain BP is degraded as compared to the antenna-domain BP due to increased correlation between the beliefs. To avoid the impairments, we propose a novel concatenated structure of beam-and antenna-domain BP layers, which allows us to benefit from the advantages of both domains while maintaining low signal processing complexity. Numerical results show the validity of our proposed method in terms of the bit error rate (BER) performance both in the coded and uncoded cases and the computational complexity.

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A novel design of multi-user sequence set for joint vehicular radar-communication based on Oppermann family

Jagannath

Guan

et al. 2023

Digital Signal Processing

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Design of Adaptively Scaled Belief in Multi-Dimensional Signal Detection for Higher-Order Modulation

Cited by 38 publications

References 32 publications

Subspace Marginalized Belief Propagation for mmWave Overloaded MIMO Signal Detection

Subspace Marginalized Belief Propagation for mmWave Overloaded MIMO Signal Detection

Concatenated Beam- and Antenna-domain Layered Belief Propagation for Large MIMO Detection

A novel design of multi-user sequence set for joint vehicular radar-communication based on Oppermann family

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