This paper analyzes the performance of discrete input distributions (coded modulation) in interference channels. This approach is motivated in part by the necessity of using coded modulation in practical systems, and in part by the potential of discrete distributions for interference alignment as well as the importance demonstrated by Dytso et al. of discrete input distributions for transmission over the 2 × 2 interference channel when treating interference as noise. The contribution of this work includes the establishment of achievable rates subject to discrete modulations. In the process, new bounds involving the minimum distance of the sum of discrete modulations have been developed that are useful for facilitating further work in this area. These bounds are then used for finding achievable rates for 3 × 3 interference channels. It is also shown that interference alignment can be efficiently employed with discrete modulations at finite SNR even with imperfect channel state information at the transmitter.

This paper investigates basic trade-offs between energy and delay in wireless communication systems using finite blocklength theory. We first assume that data arrive in constant stream of bits, which are put into packets and transmitted over a communications link. Our results show that depending on exactly how energy is measured, in general energy depends √d-1or √Vd-1log d, where d is the delay. This means on that the energy decreases quite slowly with increasing delay. Furthermore, to approach the absolute minimum of -1.59 dB on energy, bandwidth has to increase very rapidly, much more than what is predicted by infinite blocklength theory. We then consider the scenario when data arrive stochastically in packets and can be queued. We devise a scheduling algorithm based on finite blocklength theory and develop bounds for the energy-delay performance. Our results again show that the energy decreases quite slowly with increasing delay.

We pursue interference mitigation via the integration of two key ideas. First, understanding the behavior of available rates under discrete signaling which has recently been shown to be promising in the interference channel. This part calls for calculation of good bounds on post-interference mutual information under discrete signaling, as a function of the forward and cross channel gains. Second, the capacity of the interference channel is known to be very irregular, so for any target capacity there are “outage” sets that we aim to avoid by using reconfigurable antennas. For the first component, we report an analytical lower bound on the mutual information and establish a constant gap O(logγ) to capacity (excepting an outage set) that is derived using a purely discrete signaling. This result outperforms the gap reported by Dytso et al that was generated via a mixed discrete-continuous input strategy. In the second part of this work, we propose to use a reconfigurable antenna technology involving liquid metal antennas that can steer the channel away from the outage scenarios and therefore facilitate higher values of coded rates for the two-user symmetric Gaussian interference channel. The viability of the proposed technique is studied via simulations.

This paper analyzes the performance of discrete input distributions (coded modulation) in certain 3 user interference channels. This approach is motivated in part by the necessity of using coded modulation in practical systems, and in part by the potential of discrete distributions for interference alignment as well as the demonstrated importance of discrete input distributions for transmission over the 2 × 2 interference channel when treating interference as noise. The contribution of this work includes the establishment of achievable rates subject to discrete (PAM) modulations. In the process, new bounds involving the minimum distance of the sum of discrete modulations have been developed that are useful for facilitating further work in this area.

We consider a relay-aided wireless multicast channel in which all transmissions are constrained to be drawn from M-ary PAM constellations. In order to deal with heterogeneous channel conditions at different receivers, we propose a practical layered compress-and-forward (CF) scheme that utilizes scalar quantization concatenated with Slepian-Wolf coding. Exploiting the inherent unequal protection provided to different bit-planes of an M-ary PAM constellation, the layering is accomplished through an intelligent mapping of the quantization bits to the relay's transmission symbols. This allows users to adapt by extracting as many CF cooperation layers as allowed by the channel conditions. By analyzing information theoretic performance, we find that the proposed scheme performs significantly better than the traditional unlayered CF for a wide variety of channel conditions; our best results indicate a performance gap of 1.1 dB between the two.