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

Abstract

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.

User Grouping for the Uplink of Multiuser Hybrid mmWave MIMO

“…As mentioned, a specific DQLC mapping is individually applied into the G s ≤ G groups containing the users served, and therefore the parameters α i,j and i,j must conveniently be optimized for the g i users at each group. A detailed description about the DQLC implementation and parameter optimization can be found in [23], [24], [30].…”

“…In [30], in-depth treatment about this optimization is provided, where only one group of users is considered. In this work, we consider several groups and therefore the potential inter-group interference has to be taken into account in the parameter design.…”

“…In this work, we consider several groups and therefore the potential inter-group interference has to be taken into account in the parameter design. We follow an alternative approach to [30] by considering the signal-to-interference-plus-noise ratio (SINR)-affected by the inter-group interference due to the hybrid implementation of the combiner at the BS-as the metric to optimize the DQLC parameters. In the proposed setup, the symbols at the input of the demapping operation are given by…”

“…Therefore, we will use this latter decoding algorithm since it can be applied to an arbitrary number of users per group (cf. [24] or [30] for details).…”

“…• From [30], [31] it is clear that the DQLC mapping is able to improve the system performance by exploiting spatial correlation. Hence, the scheduling approach will be designed to guarantee the exploitation of the interuser correlation per group.…”