ATINA: Approximate optimality of treating interference as noise in wireless multiple-input single-output (MISO) antenna networks
Final Report Abstract
It is projected that the number of connected wireless devices will exceed 50 billion 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 the one hand, utilizes 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 project is to study the approximate optimality of one of the most simple ways of dealing with interference, namely treating interference as noise (TIN). Thus, the main objective of the project is to characterize the approximate optimality of TIN with respect to the maximum achievable rate (i.e., capacity). To this end, we consider the general downlink channel with multiple antennas with imperfect channel state information. The proposed research methods for dealing with this problem are structured in two phases, namely relay MIMO networks and cloud radio access network (C-RAN) networks. In the former, we study the capacity optimality of TIN for the case where residual self-interference (RSI) is present and a MIMO decode-and -forward (DF) relay strategy is established as a primary means of communication. We then provide a framework in which the most robust covariance matrix design is obtained. The insights obtained from this part of the project is then used in the second part, which is devoted to the signal design under the imperfect channel state information (CSI). Moreover, in this part, we study the approximate optimality of TIN for the more general setup in which there are more than one transmitter each equipped with multiple antennas. The results obtained from this task highlight the effect of the lack of channel knowledge on the approximate optimality of TIN for the multiple antenna case. Finally, we evaluate the optimality of TIN for modern system architectures like reconfigurable intelligent surface (RIS) assisted wireless channels (i.e., in combination with new algorithms) and verify the obtained results in more general models.
Publications
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"Interference mitigation via ratesplitting and common message decoding in cloud radio access networks", IEEE Access, vol. 7, pp. 80350–80365, 2019
A. Ahmad, H. Dahrouj, A. Chaaban A.Sezgin, and M.-S.Alouini
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"Rate splitting and common message decoding for MIMO C-RAN systems", 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), pp. 1–5, 2019
A. Alameer, J. Kakar, H. Dahrouj and A. Chaaban, K. Shen, A. Sezgin, T. Al-Naffouri, Tareq and M. Alouini
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"UAV-assisted C-RAN with rate splitting under base station breakdown scenarios", 2019 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 1–6, 2019
A. Alameer, J. Kakar, R. Reifert and A. Sezgin
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"Robust transceiver design for full-duplex decodeand-forward relay-assisted MIMO systems", 2020 54th Asilomar Conference on Signals, Systems, and Computers, pp. 1347-1352, 2020
H. Esmaeili and A. Kariminezhad and A. Sezgin
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"Fairness Analysis in IRS assisted C-RAN with Imperfect CSI", IEEE Global Communications Conference, Rio de Janeiro, Brazil, pp. 1–5, 2022
H. Esmaeili, A. Alameer and A. Sezgin
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"Robust Transceiver Design for IRS-Assisted Cascaded MIMO Communication Systems", Sensors, vol. 22, no. 17 pp. 6587, 2022
H. Esmaeili and A. Kariminezhad and A. Sezgin
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"Robust Transceiver Design for IRS-Assisted Cascaded MIMO Systems", IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), pp. 1–5, 2022
H. Esmaeili and A. Kariminezhad and A. Sezgin
