Constellation Design for Bit-Interleaved Coded Modulation (BICM) Systems in Advanced Broadcast Standards

Low-Complexity Lattice Reduction Demapper for Massive Order One-Dimensional Non-Uniform Constellations

“…The authors of this paper proposed in [1] the design of optimal NUCs for BICM systems. The procedure explained in [1] is followed in this work to design the 1D-NUCs.…”

“…The authors of this paper proposed in [1] the design of optimal NUCs for BICM systems. The procedure explained in [1] is followed in this work to design the 1D-NUCs. The distances between adjacent constellation points in these designed 1D-NUCs do not fulfill the requirements expressed above.All the distances between adjacent points must be multiples of dmin, and consequently, the designed 1D-NUCs are post-processed in order to fulfill the design condition.…”

“…INTRODUCTION he necessity of providing higher system capacity with the same spectral resources for the new wireless communications systems results into the birth of advanced modulation schemes. Recently, non-uniform constellations (NUC) have been proposed [1]- [3] in order to increment the bit-interleaved coding and modulation (BICM) spectral efficiency [4], [5]. Up to now, the existing NUCs can be gathered into two families: one-dimensional (1D-NUC) and two-dimensional non-uniform constellations (2D-NUC).…”

Low Complexity Adaptive Demapper for 2-D Non-Uniform Constellations

“…INTRODUCTION ncreasing spectral efficiency of wireless broadcasting systems to get close to the channel capacity upper bound represents nowadays a major goal of many research projects worldwide. Techniques such as Multiple Input Multiple Output (MIMO) [1], Rotated Constellations (RC) [2] and Non-Uniform Constellations (NUC) [3] respond to this demand providing a good tradeoff between system capacity and bandwidth usage.…”

“…As a consequence, a two-dimensional demapper (2D-demapper) must be applied to each received symbol. In addition, the number of Euclidean distances to be computed for Maximum Likelihood (ML) demapping of 2D-NUCs increases notably with respect to the one required for demapping 1D-NUCs [3]. This fact results into a significant increase in demapping complexity for 2D-NUCs when compared to 1D-NUCs.…”