Enumerative Amplitude Shaping for Energy-Efficient Wireless Transmitters
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Solution Overview
Problem
Conventional IEEE 802.11x transmitters are energy inefficient due to equal probability symbol selection, limiting transmit power reduction in dense user environments like vehicular networks, and require significant memory and computations for shaping and deshaping algorithms.
Innovation Solution
Implementing enumerative amplitude shaping with reduced memory and computational requirements by using a nonlinear-estimation process to select bounded-energy amplitude sequences and provide an index for efficient shaping and deshaping operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional equal probability symbol selection is used in IEEE 802.11x transmitters, then the implementation is simple, but energy efficiency is poor and transmit power cannot be reduced
Solution Approach 1:
The shaping algorithm is divided into pre-computed lookup tables (stored during off-line processing) and simple on-line index selection. The complex trellis construction and amplitude sequence computation are segmented into pre-processing steps, while only lightweight operations remain for real-time transmission.
Solution Approach 2:
The energy-constrained trellis construction, amplitude sequence generation, and lookup table creation are performed in advance during system initialization or off-line processing. This preliminary action eliminates the need for complex real-time computations during actual data transmission.
2Use of energy by moving object
If shaping algorithms with large memory and computations are used, then energy efficiency improves, but real-time implementation becomes difficult
Solution Approach 1:
All computationally intensive operations including trellis construction, amplitude sequence computation, and statistics calculation are performed in advance. The pre-computed results are stored in compact lookup tables, enabling rapid real-time symbol selection without sacrificing energy efficiency.
Solution Approach 2:
Instead of performing complex computations in real-time, the system creates compact copies of pre-computed amplitude sequences and trellis structures in lookup tables. The real-time operation merely involves indexing and selection from these pre-prepared data structures.
3Object-affected harmful factors
If conventional symbol selection is used, then implementation is straightforward, but interference reduction in dense user environments is limited
Solution Approach 1:
The interference reduction capability is achieved through segmented processing: pre-computation of energy-constrained sequences during initialization, storage in compact lookup tables, and simple index-based selection during transmission. This segmentation enables advanced interference management without increasing real-time complexity.
Solution Approach 2:
The system changes the selection criterion from uniform probability to energy-constrained probability based on pre-computed statistics. By modifying the selection parameters using offline-analyzed channel characteristics, the system achieves better interference reduction while keeping online operations simple.
Data Source
AI summary
Certain aspects of the disclosure are directed to a method for communicating data from a transmitting circuit to a receiving circuit over a noisy channel. The method can be performed by logic circuitry, and can include encoding data, for transmission over the noisy channel. The data can be encoded, as a shaped-coded modulation signal by shaping the signal based on an amplitude selection algorithm that leads to a symmetrical input and by constructing a trellis having a bounded-energy sequence of amplitude values selected by computing and storing a plurality of channel-related energy constraints based on use of a nonlinear-estimation process, and therein providing an index for the bounded-energy sequence of amplitudes. The method can also include receiving over the noisy channel, the shaped-coded modulation signal, and decoding the data from the shaped-coded modulation signal by using the index to reconstruct the bounded-energy sequence of amplitudes.