  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 paper, 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 the DQLC is considered to jointly exploit the
temporal and spatial correlation of the source symbols. The 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.
