Iterative Soft Interference Cancellation for Sparse BPSK Signals

Bockelmann, Carsten

doi:10.1109/lcomm.2015.2408594

Cited by 16 publications

(7 citation statements)

References 8 publications

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“…Utilizing the a posteriori LLRs generated in DEC for each user after several iterations, hard decisions can be reached to realize data detection. It should be noted that, in order to realize the data detection, the a posteriori LLRs L APP (b k (i)) is only treated as the input information of the hard decision, whereas the L APP (b k (i)) contains the activity information, but not been utilized [24]. In order to exploit the activity information, we adopt the activity detection strategy on the basis of CBC that summing up a frame of the absolute value of a posteriori LLRs produced in DEC for each user to determine active users.…”

Section: Cbc-admentioning

confidence: 99%

Multi-User Detection for Sporadic IDMA Transmission Based on Compressed Sensing

Kang

et al. 2017

Entropy

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Abstract:The Internet of Things (IoT) is placing new demands on existing communication systems. The limited orthogonal resources do not meet the demands of massive connectivity of future IoT systems that require efficient multiple access. Interleave-division multiple access (IDMA) is a promising method of improving spectral efficiency and supporting massive connectivity for IoT networks. In a given time, not all sensors signal information to an aggregation node, but each node transmits a short frame on occasion, e.g., time-controlled or event-driven. The sporadic nature of the uplink transmission, low data rates, and massive connectivity in IoT scenarios necessitates minimal control overhead communication schemes. Therefore, sensor activity and data detection should be implemented on the receiver side. However, the current chip-by-chip (CBC) iterative multi-user detection (MUD) assumes that sensor activity is precisely known at the receiver. In this paper, we propose three schemes to solve the MUD problem in a sporadic IDMA uplink transmission system. Firstly, inspired by the observation of sensor sparsity, we incorporate compressed sensing (CS) to MUD in order to jointly perform activity and data detection. Secondly, as CS detection could provide reliable activity detection, we combine CS and CBC and propose a CS-CBC detector. In addition, a CBC-based MUD named CBC-AD is proposed to provide a comparable baseline scheme.

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Section: Cbc-admentioning

confidence: 99%

Multi-User Detection for Sporadic IDMA Transmission Based on Compressed Sensing

Kang

et al. 2017

Entropy

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“…Note that ( 11) and ( 12) are used in the iterative decoding part such as in (7) and the calculation of µ ς t|(k,j) and ξ ς t|(k,j) .…”

Section: B Joint Active User Detection and Decoding Algorithmmentioning

confidence: 99%

“…Note that the active user detection in sparse system has also been investigated in [5]- [7]. Compared with these works, the advantages of our scheme are two-fold: (i) Previous works require that the channel state information (CSI) are available to the AP while our scheme does not, which makes sense for short packet transmission in IoT since the acquisition of CSI often incurs large amount of signalling; (ii) Unlike the previous works that apply the relatively complicated maximum a posteriori probability (MAP) detection, the proposed BP-based joint detection and decoding is of affordably low complexity, which makes it viable for massive access.…”

Section: Introductionmentioning

confidence: 99%

Grant-Free Rateless Multiple Access: A Novel Massive Access Scheme for Internet of Things

et al. 2016

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Abstract-Rateless Multiple Access (RMA) is a novel nonorthogonal multiple access framework that is promising for massive access in Internet of Things (IoT) due to its high efficiency and low complexity. In the framework, after certain registration, each active user respectively transmits to the access point (AP) randomly based on an assigned random access control function (RACf) until receiving an acknowledgement (ACK). In this work, by exploiting the intrinsic access pattern of each user, we propose a grant-free RMA scheme, which no longer needs the registration process as in the original RMA, thus greatly reduces the signalling overhead and system latency. Furthermore, we propose a low-complexity joint iterative detection and decoding algorithm in which the channel estimation, active user detection, and information decoding are done simultaneously. Finally, we propose a method based on density evolution (DE) to evaluate the system performance.Index Terms-Internet of Things (IoT), massive access, nonorthogonal multiple access.

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“…But kernel function selection and parameter setting under different application background conditions, and conflict between time frequency resolutions restrict performance of time-frequency analysis (TFA) method. Utilizing Compressed Sensing (CS) theory, literature [26] made sampling to BPSK signal with sampling frequency lower than Nyquist, which decreases demand to storage resource, improves processing speed and weakens effect of Iterative Soft Interference on BPSK signal. But in accordance with CS theory, signal will possess sparsity and signal is not concerned with sparsity space where it is located, which restricts application of the method in reality.…”

Section: Introductionmentioning

confidence: 99%

Detection Algorithm of BPSK Signal of Parameter-Adjusted Bistable Stochastic Resonance Model Based on Scale Change

et al. 2020

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Given that signal is weakened to a certain extent in the process of noise suppression using mainstream method, and that new noise is introduced by signal processing system, causing the decrease of detection performance, to improve the performance of detection to BPSK signal under the condition of strong noise and no prior information, the detection algorithm of BPSK signal of bistable stochastic resonance model based on scale change is proposed in this study. Using classical bistable stochastic resonance (BSR) system, only low-amplitude and low-frequency periodic signal can be processed. Scale change is first made to BSR in this study, verifying that BSR can be applied to high-frequency BPSK signal under high sampling frequency condition, and nonlinear threshold detection system is designed following Neyman-Pearson criterion to deduce and quantitatively show error rate of detector. Besides, complete flow for signal detection was built by taking it as feedback quantity to adjust the system parameters adaptively. Scale change feasibility and applicability of algorithm proposed in this study were verified through simulation experiment, which lays the theoretical basis for the detection of weak BPSK signal under low signal-to-noise ratio (SNR).

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Iterative Soft Interference Cancellation for Sparse BPSK Signals

Cited by 16 publications

References 8 publications

Multi-User Detection for Sporadic IDMA Transmission Based on Compressed Sensing

Multi-User Detection for Sporadic IDMA Transmission Based on Compressed Sensing

Grant-Free Rateless Multiple Access: A Novel Massive Access Scheme for Internet of Things

Detection Algorithm of BPSK Signal of Parameter-Adjusted Bistable Stochastic Resonance Model Based on Scale Change

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