All you need is feedback: Communication with block attention feedback codes
Deep learning based channel code designs have recently gained interest as an alternative to conventional coding algorithms, particularly for channels for which existing codes do not provide effective solutions. Communication over a feedback channel is one such problem, for which promising results have recently been obtained by employing various deep learning architectures. In this paper, we introduce a novel learning-aided code design for feedback channels, called generalized block attention feedback (GBAF) codes, which i) employs a modular architecture that can be implemented using different neural network architectures; ii) provides order-of-magnitude improvements in the probability of error compared to existing designs; and iii) can transmit at desired code rates.
Code (0)
등록된 구현이 없습니다.
Tasks
AllDeep LearningSimilar Papers 제목 키워드 기반
AttentionCode: Ultra-Reliable Feedback Codes for Short-Packet Communications
Ultra-reliable short-packet communication is a major challenge in future wireless networks with critical applications. To achieve ultra-reliable communications beyond 99.999%, this paper envisions a new interaction-based…
Feedback is Good, Active Feedback is Better: Block Attention Active Feedback Codes
Deep neural network (DNN)-assisted channel coding designs, such as low-complexity neural decoders for existing codes, or end-to-end neural-network-based auto-encoder designs are gaining interest recently due to their imp…
Feedback Lunch: Learned Feedback Codes for Secure Communications
We consider reversely-degraded secure-communication channels, for which the secrecy capacity is zero if there is no channel feedback. Specifically, we focus on a seeded modular code design for the block-fading Gaussian w…
Robust Non-Linear Feedback Coding via Power-Constrained Deep Learning
The design of codes for feedback-enabled communications has been a long-standing open problem. Recent research on non-linear, deep learning-based coding schemes have demonstrated significant improvements in communication…
DecoderDeep LearningCSI Feedback with Model-Driven Deep Learning of Massive MIMO Systems
In order to achieve reliable communication with a high data rate of massive multiple-input multiple-output (MIMO) systems in frequency division duplex (FDD) mode, the estimated channel state information (CSI) at the rece…
Deep Learning