Lattice codes are elegant and powerful structures that not only can achieve the capacity of the AWGN channel but also are a key ingredient to many multiterminal schemes that exploit linearity properties. However, constructing lattice codes that can realize these benefits with low complexity is still a challenging problem. In this paper, efficient encoding and decoding algorithms are proposed for multilevel binary LDPC lattices constructed via Construction D' whose complexity is linear in the total number of coded bits. Moreover, a generalization of Construction D' is proposed that relaxes some of the nesting constraints on the component codes, leading to a simpler and improved design. Based on this construction, low-complexity multilevel LDPC lattices are designed whose performance under multistage lattice decoding is comparable to that of polar lattices on the power-unconstrained AWGN channel and close to that of conventional (non-lattice) coded modulation schemes on the power-constrained AWGN channel.
Multilevel lattice constructions based on binary codes are potentially harder to design, but have the promise of complexity that scales linearly with the number of levels. Moreover, they are known to be AWGN-good under multistage decoding @cite_38 . Construction D has been used in @cite_11 to produce turbo lattices and in @cite_12 to construct polar lattices; the latter are shown to be AWGN-good with encoding and decoding complexity @math . Construction D has also been used in @cite_23 to construct spatially-coupled LDPC lattices, which were shown to be AWGN-good under multistage belief propagation decoding. However, both the encoding and the cancellation step that has to be performed at each decoding stage rely on the generator matrices of the component LDPC codes, which are generally dense, leading to an overall high complexity.
@cite_38 @cite_23 @cite_12 @cite_11
2098653764 1512015702 2963192682 2137697643
In this paper, we propose a new class of lattices constructed from polar codes, namely polar lattices, to achieve the capacity @math of the additive white Gaussian-noise (AWGN) channel for any signal-to-noise ratio (SNR). Our construction follows the multilevel approach of , where on each level we construct a capacity-achieving polar code. The component polar codes are naturally nested, thereby fulfilling the requirement of the multilevel lattice construction. We prove that polar lattices are AWGN-good, in the sense that the error probability (for infinite lattice decoding) vanishes for any fixed volume-to-noise ratio (VNR) greater than @math . Furthermore, using the technique of source polarization, we propose discrete Gaussian shaping over the polar lattice to satisfy the power constraint. The proposed polar lattices permit low-complexity multistage successive cancellation decoding. Both the construction and shaping are explicit, and the overall complexity of encoding and decoding is @math for any fixed target error probability. We address an open question, regarding whether a lattice code with lattice decoding (as opposed to maximum-likelihood (ML) decoding) can achieve the additive white Gaussian noise (AWGN) channel capacity. We first demonstrate how minimum mean-square error (MMSE) scaling along with dithering (lattice randomization) techniques can transform the power-constrained AWGN channel into a modulo-lattice additive noise channel, whose effective noise is reduced by a factor of spl radic (1+SNR SNR). For the resulting channel, a uniform input maximizes mutual information, which in the limit of large lattice dimension becomes 1 2 log (1+SNR), i.e., the full capacity of the original power constrained AWGN channel. We then show that capacity may also be achieved using nested lattice codes, the coarse lattice serving for shaping via the modulo-lattice transformation, the fine lattice for channel coding. We show that such pairs exist for any desired nesting ratio, i.e., for any signal-to-noise ratio (SNR). Furthermore, for the modulo-lattice additive noise channel lattice decoding is optimal. Finally, we show that the error exponent of the proposed scheme is lower bounded by the Poltyrev exponent. A novel construction of lattices is proposed. This construction can be thought of as Construction A with codes that can be represented as the Cartesian product of L linear codes over Fp1 , . . . ,FpL , respectively; hence, is referred to as the product construction. The existence of a sequence of such lattices that are good for quantization and Poltyrev-good under multistage decoding is shown. This family of lattices is then used to generate a sequence of nested lattice codes which allows one to achieve the same computation rate of Nazer and Gastpar for computeand-forward under multistage decoding, which is referred to as lattice-based multistage compute-and-forward. Motivated by the proposed lattice codes, two families of signal constellations are then proposed for the separation-based compute-and-forward framework proposed by together with a multilevel coding multistage decoding scheme tailored specifically for these constellations. This scheme is termed separation-based multistage compute-and-forward and is shown having a complexity of the channel coding dominated by the greatest common divisor of the constellation size (may not be a prime number) instead of the constellation size itself. In this work we introduce and establish the concept of turbo lattices. We employ a routine method for constructing lattices, called Construction D, to construct turbo lattices. This kind of construction needs a set of nested linear codes as its underlying structure. We benefit from turbo codes as our bases codes. Therefore, we first build a set of nested turbo codes based on nested interleavers and nested convolutional codes. Then by means of these codes, along with construction D, we construct turbo lattices. Several properties of Construction D lattices and specially many characteristics of turbo lattices including the minimum distance, coding gain, kissing number and the probability of error under a maximum likelihood decoder over AWGN channel are investigated.