Analog Transmission of Correlated Sources Over Fading SIMO Multiple Access Channels

Suárez-Casal, Pedro; Fresnedo, Óscar; Castedo, Luis; Garcia-Frías, Javier

doi:10.1109/tcomm.2017.2695197

Cited by 9 publications

(28 citation statements)

References 26 publications

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“…The proposed decoder relies on the use of a sphere decoder to lower the overall complexity while computing the numerical integrals involved in the MMSE decoding. Although the approach resembles that in [12], the transformations over the original mapping function and the mathematical derivation of the searching lattice are different. • A practical optimization of the DQLC mapping parameters which enables its utilization on scenarios with a moderate number of transmit users.…”

Section: A Contributionsmentioning

confidence: 99%

“…Sphere decoding is a general strategy to search for the closest vectors in a lattice and it was originally proposed to detect digital signals in MIMO transmissions [11]. This strategy has already been applied to lower the computational cost of the MMSE estimation when transmitting analog symbols using modulo mappings [12]. In this paper, we mathematically derive the lattice corresponding to DQLC-based mappings and apply the sphere decoder to the obtained lattice.…”

Section: Introductionmentioning

confidence: 99%

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Transmission of Spatio-Temporal Correlated Sources Over Fading Multiple Access Channels With DQLC Mappings

Fresnedo

Suárez-Casal

Castedo

2019

IEEE Trans. Commun.

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The design of zero-delay Joint Source-Channel Coding (JSCC) schemes for the transmission of correlated information over fading Multiple Access Channels (MACs) is an interesting problem for many communication scenarios like Wireless Sensor Networks (WSNs). Among the different JSCC schemes so far proposed for this scenario, Distributed Quantizer Linear Coding (DQLC) represents an appealing solution since it is able to outperform uncoded transmissions for any correlation level at high Signal-to-Noise Ratios (SNRs) with a low computational cost. In this work, we extend the design of DQLC-based schemes for fading MACs considering sphere decoding to make the optimal Minimum Mean Squared Error (MMSE) estimation computationally affordable for an arbitrary number of transmit users. The use of sphere decoding also allows to formulate a practical algorithm for the optimization of DQLC-based systems. Finally, non-linear Kalman Filtering for DQLC is considered to jointly exploit the temporal and spatial correlation of the source symbols. Results of computer experiments show that the proposed DQLC scheme with the Kalman Filter decoding approach clearly outperforms uncoded transmissions for medium and high SNRs.

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Section: A Contributionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Transmission of Spatio-Temporal Correlated Sources Over Fading Multiple Access Channels With DQLC Mappings

Fresnedo

Suárez-Casal

Castedo

2019

IEEE Trans. Commun.

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“…Equation (33) determines the maximum number of bits which can be transmitted at each channel use with an arbitrarily low probability of error, whereas (31) determines the minimum number of bits required to achieve the distortion given by the parameter θ. Since we are transmitting two source symbols in two channel uses, ( 31) and ( 33) can be equated directly, searching for the parameter θ which satisfies such equality.…”

Section: A Performance Bound For Cfmentioning

confidence: 99%

Transmission of Analog Information Over the Multiple Access Relay Channel Using Zero-Delay Non-Linear Mappings

2019

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We consider the zero-delay encoding of discrete-time analog information over the Multiple Access Relay Channel (MARC) using non-linear mapping functions. On the one hand, zero-delay nonlinear mappings are capable to deal with the multiple access interference (MAI) caused by the simultaneous transmission of the information. On the other, the relaying operation is a Decode-and-Forward (DF) strategy where the decoded messages are merged into a single message using a specific continuous mapping depending on the correlation level of the source information. At the receiver, an approximated Minimum Mean Squared Error (MMSE) decoder is developed to obtain an estimate of the transmitted source symbols which exploits the information received from the relay node in combination with the messages received from the transmitters through the direct links. The resulting system provides better performance than the other alternative encoding strategies for the MARC with similar complexity and delay and also approaches the performance of theoretical strategies which require a significantly higher delay and computational cost.INDEX TERMS Combined source-channel coding, relay networks, multiuser channels, network coding.

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“…We boldly and explicitly contrast our contributions to the state-of-the-art in Table II and detail them below: 1 We reduce the complexity of SISO CS decoding by using a tree search to find the most likely combination of the source signal and associated sensor values before using the SD to find the set of likely alternative hypotheses, in order to glean high quality extrinsic information, which can be iteratively exchanged with the concatenated channel decoder. Unlike the traditional SD routinely used for JSCC or for MIMO detection based on the distance between adjacent points [27]- [29], the proposed scheme performs tree search-based SD relying on the input Logarithmic-Likelihood Ratios (LLRs). Furthermore, our scheme exploits the additional constraints imposed by the sparsity upper bound K and the presence/absence of connectivity between the source signals and sensors, which make the application of SD a challenge.…”

Section: Introductionmentioning

confidence: 99%

Tree-Search Techniques for Joint Iterative Compressive Sensing and LDPC Decoding in Wireless Sensor Networks

Chen

Wang

et al. 2023

IEEE Sensors J.

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Novel techniques are conceived for joint Compressive Sensing (CS) and Low-Density Parity Check (LDPC) coding in Wireless Sensor Networks (WSNs), namely a Soft-Input Soft-Output (SISO) tree search Sphere Decoding (SD) technique, and a SISO Hamming Distance (HD) based solution. Factor graphs are utilized to describe the connectivity between the signals and sensors, as well as with the LDPC codes. In the Fusion Center (FC), the factor graphs may be used for iterative joint LDPC-CS decoding, in order to recover the signals observed. However, the CS decoder of the FC suffers from high complexity, if the exhaustive Maximum A posteriori (e-MAP) technique is employed, which considers all possible combinations of source signals detected by each of the associated sensors. Hence, in the proposed SD and HD schemes only the more likely combinations of source signals are tested for reducing the CS decoding complexity. More specifically, a tree search technique is used in the first step to find the most likely combination of source signal values.Then, in the second step, the proposed SD continues the tree search to find a set of alternative hypotheses. This facilitates the generation of high quality extrinsic information, which may be iteratively exchanged with the LDPC decoder. By contrast, in the HD approach, the second step obtains the alternative hypotheses within a certain HD of the most likely source signal combination. Both our BLock Error Rate (BLER) results and Extrinsic Information Transfer (EXIT) charts show that the proposed SD and HD techniques approach the performance of the full-search e-MAP approach at a significantly reduced complexity. In particular, we show the e-MAP solution is about 56 times more complex than the SD approach and around 210 times more complex than the HD approach. Compared to a Separate Source-Channel Coding (SSCC) hard information benchmarker, the proposed SISO schemes improve the decoding performance by about 1.7 dB. Furthermore, the SISO schemes allow the iterations inside the CS decoding to eliminate the error floors and obtain a further 2.45 dB gain.

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Analog Transmission of Correlated Sources Over Fading SIMO Multiple Access Channels

Cited by 9 publications

References 26 publications

Transmission of Spatio-Temporal Correlated Sources Over Fading Multiple Access Channels With DQLC Mappings

Transmission of Spatio-Temporal Correlated Sources Over Fading Multiple Access Channels With DQLC Mappings

Transmission of Analog Information Over the Multiple Access Relay Channel Using Zero-Delay Non-Linear Mappings

Tree-Search Techniques for Joint Iterative Compressive Sensing and LDPC Decoding in Wireless Sensor Networks

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