ATINA: Approximate optimality of treating interference as noise in wireless multiple-input single-output (MISO) antenna networks

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It is projected that the number of connected wireless devices will exceed 50 billions by 2020. Thus, system designers are confronted with the challenge of managing the resulting interference those devices cause to each other. This calls for schemes, which on one hand utilize the limited resources such as time, frequency, and power optimally. On the other hand, the computational complexity of those schemes needs to be kept at a reasonable level so that they can be deployed in practice. In consequence, the goal of the planned project is studying the approximate optimality of one of the most simple ways dealing with interference, namely treating interference as noise (TIN).Thus, the main objective of the project is to find the necessary andsufficient conditions on the approximate optimality of TIN with respect to the maximum achievable rate (i.e., capacity). To this end, we consider the general soft-handoverchannel with multiple antennas with imperfect channel state information. The proposed research methods for dealing with this problem arestructured in three work packages which are planned for three years.In work package 1, we study the capacity optimality of TIN for thesoft-handover channel with single antenna in which the output of thesetup is a linear deterministic function (noiseless setup) of the input.The insights obtained from the first work package will be used in thesecond work package which is devoted to the noisy soft-handover channel.Moreover, in this work package, we study the approximate optimality of TIN for themore general setup in which the nodes are equipped with multi antennas.The results obtained from this task highlight the effect the lack of channel knowledge on the approximate optimality of TIN for the multiple antenna case.Finally, in work package 3, we implement a system level simulator for the cross-layer evaluation (i.e., in combination with scheduling algorithms) and verification of the obtained results in more general models.Different user modeling methods are evaluated, starting with static user deployment and later on with mobile users. In addition to this, we use the system level simulator to assess the approximateoptimality of TIN in terms of useful throughput (goodput), which takes theuser coordination costs in terms of required feedback into account.