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We propose a novel soft-output joint channel estimation and data detection (JED) algorithm for multiuser (MU) multiple-input multiple-output (MIMO) wireless communication systems. Our algorithm approximately solves a maximum a-posteriori JED optimization problem using deep unfolding and generates soft-output information for the transmitted bits in every iteration. The parameters of the unfolded algorithm are computed by a hyper-network that is trained with a binary cross entropy (BCE) loss. We evaluate the performance of our algorithm in a coded MU-MIMO system with 8 basestation antennas and 4 user equipments and compare it to state-of-the-art algorithms separate channel estimation from soft-output data detection. Our results demonstrate that our JED algorithm outperforms such data detectors with as few as 10 iterations. 

We propose a joint channel estimation and data detection (JED) algorithm for cell-free massive multi-user (MU) multiple-input multiple-output (MIMO) systems. Our algorithm yields improved reliability and reduced latency while minimizing the pilot overhead of coherent uplink transmission. The proposed JED method builds upon a novel non-convex optimization problem that we solve approximately and efficiently using forward- backward splitting. We use simulation results to demonstrate that our algorithm achieves robust data transmission with more than 3x reduced pilot overhead compared to orthogonal training in a 128 antenna cell-free massive MU-MIMO system in which 128 users transmit data over 128 time slots. 

Recent years have witnessed the rapid development of sustainable materials. Along this line, developing biodegradable or recyclable soft electronics is challenging yet important due to their versatile applications in biomedical devices, soft robots, and wearables. Although some degradable bulk hydrogels are directly used as the soft electronics, the sensing performances are usually limited due to the absence of distributed conducting circuits. Here, sustainable hydrogel‐based soft electronics (HSE) are reported that integrate sensing elements and patterned liquid metal (LM) in the gelatin–alginate hybrid hydrogel. The biopolymer hydrogel is transparent, robust, resilient, and recyclable. The HSE is multifunctional; it can sense strain, temperature, heart rate (electrocardiogram), and pH. The strain sensing is sufficiently sensitive to detect a human pulse. In addition, the device serves as a model system for iontophoretic drug delivery by using patterned LM as the soft conductor and electrode. Noncontact detection of nearby objects is also achieved based on electrostatic‐field‐induced voltage. The LM and biopolymer hydrogel are healable, recyclable, and degradable, favoring sustainable applications and reconstruction of the device with new functions. Such HSE with multiple functions and favorable attributes should open opportunities in next‐generation electronic skins and hydrogel machines.