Next-generation wireless networks aim to enable order-of-magnitude increases in connectivity, capacity, and speed. Such a goal can be achieved in part by utilizing larger frequency bandwidth or by deploying denser base stations. As the number of wireless devices is exploding, however, it is inevitable that multiple devices communicate over the same time and same spectrum. Consequently, improving the spectral efficiency in wireless networks with multiple senders and receivers becomes the key challenge. This dissertation investigates low-complexity channel coding techniques that implement canonical random coding schemes in network information theory, such as universal channel coding, superposition coding, rate-splitting, successive cancellation, simultaneous decoding, decode-forward relaying, compress-forward relaying, and Slepian--Wolf coding. In representative communication scenarios, such as compound channels, interference channels, broadcast channels, and relay channels, the proposed channel coding techniques achieve the best known information theoretic performance, some utilizing the recently invented polar codes and some making use of the commercial off-the shelf codes, e.g., turbo and LDPC codes. These techniques have a potential to become important building blocks towards a general theory of channel coding techniques for the next-generation high-spectral-efficiency, low-power, broad-coverage wireless communication.