Future wireless access networks aim to simultaneously support a large number of devices with heterogeneous service requirements, including data rates, error rates, and latencies. While achievable rate and capacity results exist for Gaussian broadcast channels in the asymptotic blocklength regime, the characterization of second-order achievable rate regions for heterogeneous blocklength constraints is not available. Therefore, we investigate a two-user Gaussian broadcast channel (GBC) with heterogeneous blocklength constraints, specified according to users’ channel output signal-to-noise ratios (SNRs). We assume that the user with higher output SNR has a shorter blocklength constraint. We show that with sufficiently large output SNR, the stronger user can perform the early decoding (ED) technique to decode and subtract the interference via successive interference cancellation (SIC). To achieve this goal, we derive an explicit lower bound on the necessary number of received symbols for a successful ED, using an independent and identically distributed Gaussian input. The second-order rate region is also derived. Numerical results show that ED can outperform the hybrid non-orthogonal multiple access scheme when the stronger channel is sufficiently better than the weaker one. Under the considered setting, about 7-dB SNR gain can be achieved compared to treating interference as noise. These results show that ED with SIC is a promising technique for future wireless networks.

Future wireless access networks will simultaneously support a large number of devices with heterogeneous service requirements. These include data rates, error rates, and latencies. While capacity results exist for Gaussian broadcast channels in the asymptotic regime, the characterization of second-order achievable rate region for different blocklength constraints is not available. Therefore, we investigate a two-user Gaussian broadcast channel (GBC) with heterogeneous blocklength constraints, specified according to users’ channel output signal to noise ratios (SNRs) under a maximal input power constraint and an average error probability constraint. We show that with sufficiently large output SNR, the stronger user can invoke the technique named early decoding (ED) to decode the interference. Then the successive interference cancellation (SIC) is performed. We derive the rate region of the considered setting with individual and also sum power constraints and compare with the hybrid non-orthogonal multiple access (HNOMA) scheme. Numerical results show that under sum power constraint, ED has a larger rate region than HNOMA at the region where the weaker user’s rate is sufficiently large, when the gain of the better channel is sufficiently larger than the weaker one. The above observation makes ED with SIC a promising technique for future wireless networks.

A new automatic search methodology for model selection of support vector machines, based on the GA-based tuning algorithm, is proposed to search for the adequate hyperparameters of SVMs. In our method, each chromosome indicates a group of hyperparameters, and the population is a collection of chromosomes. Experimental results show that our method performs superiorly on time cost, performance and stability. Our algorithm requires only the evaluation of an objective function to guide its search with no additional derivative or auxiliary knowledge required. In addition, the encoding of chromosomes makes the implementation of multiple hyperparameters tuning simpler.