Gaussian Message Passing Detection With Constant Front-Haul Signaling for Cell-Free Massive MIMO

Hua, Li; Dong, Yuanyuan; Gong, Caihong; Wang, Xiyuan; Dai, Xiaoming

doi:10.1109/tvt.2022.3224002

Cited by 4 publications

(1 citation statement)

References 15 publications

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“…By making w k the subject of (58), we obtain (15). The terms E{y R s * k } and E{y R y H R } are given by ( 16) and (17), where…”

Section: A Derivation Of the Proposed Centralized Detectormentioning

confidence: 99%

Centralized and Decentralized IDD Schemes for Cell-Free Massive MIMO Systems: AP Selection and LLR Refinement

Ssettumba,

Shao,

Landau

et al. 2024

IEEE Access

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In this paper, we propose iterative interference cancellation schemes with access points selection (APs-Sel) for cell-free massive multiple-input multiple-output (CF-mMIMO) systems. Closedform expressions for centralized and decentralized linear minimum mean square error (LMMSE) receive filters with APs-Sel are derived assuming imperfect channel state information (CSI). Based on the derived expressions, insights are drawn and general expressions are devised for several cases, namely: firstly, MMSE-SIC filter for the non-scalable CF-mMIMO that uses all APs. Secondly, an MMSE-SIC filter assuming perfect channel state information. Thirdly, in this case we assume no interference cancellation and the linear MMSE filter is obtained. Additionally, we formulate a new Gaussian approximation of the likelihood function by deriving new closed-form expressions for the second order statistics (mean and variance) of the detected signal parameters in presence of channel estimation errors, APs-Sel matrix and multi-user interference (MUI). Since the MMSE-SIC filter experiences error propagation due to erroneous decisions from the previous stages, we develop a list-based detector based on LMMSE receive filters for CF-mMIMO systems that exploits interference cancellation and the constellation points to mitigate the error propagation that occurs in conventional MMSE-SIC receivers. An iterative detection and decoding (IDD) scheme that employs low-density parity-check codes is then developed. Moreover, log-likelihood ratio (LLR) refinement strategies based on censoring and a linear combination of local LLRs are proposed to improve the network performance. We assess the proposed centralized and decentralized IDD schemes against existing approaches in terms of bit error rate performance, complexity, and signaling under perfect CSI and imperfect CSI and verify the superiority of the distributed IDD architecture with LLR refinements.INDEX TERMS Cell-free massive MIMO systems, centralized processing, decentralized processing, iterative detection and decoding, list-based detectors.

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“…By making w k the subject of (58), we obtain (15). The terms E{y R s * k } and E{y R y H R } are given by ( 16) and (17), where…”

Section: A Derivation Of the Proposed Centralized Detectormentioning

confidence: 99%

Centralized and Decentralized IDD Schemes for Cell-Free Massive MIMO Systems: AP Selection and LLR Refinement

Ssettumba,

Shao,

Landau

et al. 2024

IEEE Access

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Signalling overhead diminution in M-MIMO using NOMA transmission

Imran,

Hayat,

Ngah

2024

Discov Appl Sci

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With the increase in demand for mobile and Internet of Things devices, Orthogonal Multiple Access (OMA) cannot manage the maximum number of users. In this technique, the number of radio frequencies must be equivalent to the number of users. It causes to increase in signalling overhead. Therefore, it requires special attention to reduce the signalling overhead to escalate the spectral and energy efficiency. This paper investigates different Non Orthogonal Multiple Access (NOMA) techniques, and the results are compared with OMA techniques. A novel NOMA technique Multi User Shared Access (MUSA) is applied. It adjusts maximum users and has good spectral and energy efficiency compared to OMA techniques. In this proposed technique, maximum complex spreading codes are generated for the users and each user picks that code and transmits its data at the same radio frequency chain. The proposed scheme MUSA-NOMA has 12.8% more energy efficiency and 6.51% spectral efficiency compared to SCMA-NOMA and 32% more energy efficiency and 18.5% spectral efficiency compared to OMA. Article highlights Imagine you're using your phone in a crowded area where many people are also trying to connect, signalling congestion will occur. In traditional setups, it is difficult to manage everyone's signals. Instead of dealing with each person's signal separately, NOMA allows the communication system to treat similar groups together, streamlining the process. It's like having group discussions instead of one-on-one talks, making the whole communication setup more efficient and less complicated. This way, your phone and the network can handle many connections more smoothly, providing a better experience for everyone.

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