We apply coset codes to adaptive modulation in fading channels. Adaptive modulation is a powerful technique to improve the energy efficiency and increase the data rate over a fading channel. Coset codes are a natural choice to use with adaptive modulation since the channel coding and modulation designs are separable. Therefore, trellis and lattice codes designed for additive white Gaussian noise (AWGN) channels can be superimposed on adaptive modulation for fading channels, with the same approximate coding gains. We first describe the methodology for combining coset codes with a general class of adaptive modulation techniques. We then apply this methodology to a spectrally efficient adaptive M-ary quadrature amplitude modulation (MQAM) to obtain trellis-coded adaptive MQAM. We present analytical and simulation results for this design which show an effective coding gain of 3 dB relative to uncoded adaptive MQAM for a simple four-state trellis code, and an effective 3.6-dB coding gain for an eight-state trellis code. More complex trellis codes are shown to achieve higher gains. We also compare the performance of trellis-coded adaptive MQAM to that of coded modulation with built-in time diversity and fixed-rate modulation. The adaptive method exhibits a power savings of up to 20 dB.

Recent literature presents methods for the analysis of concatenated coding schemes by solely characterizing the behavior of the component codes [4], [12], [16], [9], [7]. Component codes are analyzed either analytically using unique properties of special component codes, e.g., single--parity--check code or accumulator, or via simulations.

Multilevel coding (MLC) schemes with powerful softly decodable component codes like turbo codes allow very power and bandwidth efficient digital communication [WH95, FHW96, WFH97a]. But the use of the non-- quantized channel output in each stage of the multistage decoding procedure leads to highly complex receivers. In this paper, the employment of hard decision decoding at several coding levels is proposed as a very efficient way to save complexity. It turns out that, for Ungerbock's labeling of signal points, the performance loss compared to soft decision decoding (in terms of capacity of the equivalent binary channel as well as in simulations) is only about 0.13 dB for ASK transmission over the AWGN channel, when hard decision decoding is employed at all but the lowest level. If error--correction techniques are exclusively employed, an MLC approach with ` individual binary error--correcting codes is recommended. 1 Introduction Multilevel coding (MLC) together with the relatively lo...