We derive inner and outer bounds on the capacity region for a class of three-user partially connected interference channels. We focus on the impact of topology, interference alignment, and interplay between interference and noise. The representative channels we consider are the ones that have clear interference alignment gain. For these channels, Z-channel type outer bounds are tight to within a constant gap from capacity. We present near-optimal achievable schemes based on rate-splitting, lattice alignment, and successive decoding.

This paper presents a novel retransmission strategy for communication networks based on index coding. The particular example of OFDMA downlink networks is taken to illustrate its efficacy. The benefits and challenges in using index coding as a transmission strategy are highlighted. The paper concludes with characterization of expected index coding gain in terms of channel parameters.

We develop achievable sum rate expressions for the Gaussian X channel at finite SNR using layered lattice coding with interference alignment. For different regimes of channel parameter h, we consider different decoding strategies including successive decoding and compute-and-forward decoding. For some regimes of h, we characterize the sum-rate capacity to within constant bits by using successive decoding. For a set of h that satisfy certain feasibility conditions, we show that compute-and-forward decoding outperforms a timesharing MAC-based lower bound. However, we find that the direct application of compute-and-forward results in high sensitivity of computation rates to the variation of h. Therefore, we introduce a channel steering method to significantly reduce the fluctuation in achievable sum-rate and consistently achieve high rates. We subsequently compare the achievable sum-rate with a new upper bound to demonstrate the value of channel steering.

Communication can consume a significant fraction of the energy for many simple sensor devices for which battery life is an important consideration in deployment. Battery power is consumed not only by transmit power amplifier but also in the radio frequency circuits and digital processors during transmission and reception. When communication requirements are bursty, many devices incorporate a `sleep' state where the circuit power consumption is also reduced by turning circuits off. Delaying transmission can allow devices to sleep more and conserve energy. We consider the optimal tradeoff between receiver energy consumption and average throughput, and derive insights on multi-user downlink communication. We reformulate the problem with generalized power constraints on the transmitter's and the receiver's power consumption: depending on their states, either transmit/receive or sleep, they consume different amounts of power. We show how these changes of power constraints affect average spectral efficiency. In Gaussian broadcast channels, taking into account the receivers' power constraints, we show that multi-user transmission schemes, previously proven to be optimal for maximizing spectral efficiency, such as superposition coding and dirty paper coding (DPC) are not always optimal. We characterize the condition, under which these schemes remain optimal, in terms of receivers' power constraints. These models are suited for machine-to-machine (M2M) communications and wireless sensor networks where 1) transmitters and/or receivers are battery-powered devices, 2) their locations are static once deployed, and 3) their data characteristic is not delay-sensitive.

In this paper, we consider a parallel relay network where two relays cooperatively help a source transmit its message to a destination. We assume the source and the destination nodes are equipped with multiple antennas. Three basic schemes and their achievable rates are studied: Decode-and-Forward (DF), Amplify-and-Forward (AF), and Compress-and-Forward (CF). For the DF scheme, the source transmits two private signals, one for each relay, where dirty paper coding (DPC) is used between the two private streams, and a common signal for both relays. The relays make efficient use of the common information to introduce a proper amount of correlation in the transmission to the destination. We show that the DF scheme achieves the capacity under certain conditions. We also show that the AF and CF schemes are asymptotically optimal in the high relay power limit if the relays-to-destination channel is full rank. The relative advantages of the three schemes are discussed with numerical results.