## Final Report Summary - IAWICOM (Interference Aligned Wireless Communications)

The objective of this project is to study a new radical idea that would enable a much higher data throughput than previously thought possible in multiuser wireless communications. Initially, we were motivated to investigate interference alignment, which attracted a lot of attention in the communication scientific community. However, at the start of the project, a new concept, known as massive MIMO, appeared with more fruitful prospects. Massive MIMO means a large excess of antennas at the base station, which makes it possible to design low-complexity linear signal processing strategies that are well matched to the propagation channel in order to maximize system capacity. In fact, they have many advantages which come by making the crucial assumption that the squared Euclidean norm of the channel vector of each user grows as O(M), whereas the inner products between channel vectors of different users grow at a lesser rate. Thus, we have tried to focus on both techniques, which appear many common advantages. In particular, this project has dealt with the performance analysis of both methods. There are many outcomes by this project that are supposed to vastly improve the quality and efficiency of existing communication systems, and contribute to the affirmation of Europe as the foremost leader in information and communication technologies. Notably, not only the resulting models schemes of interference alignment , but also of massive MIMO target to reduce energy consumption and radiation, making future telecommunications more environmentally friendly.

The goal is to develop new methods as well as integrate state-of-the-art methods in interference alignment and massive MIMO. Both concepts have emerged as new solutions to the interference problem. Especially, the latter one achieves to cancel out the inter-user and inter-cell interference. The anticipated solutions will be validated by simulations. The results will be published in prominent journals and conferences after being by reliable and respectful reviewers. The proposed approaches will establish new directions towards to more realistic systems that aim to be energy efficient and increase the throughput of the system.

Having completed the half-life of the project and advancing into the 2nd and final year provides us with a sufficient sample with respect to meeting the project’s objectives. The work performed since the beginning of the project has already led to a number of publications, ahead of the scheduled timeframe. The latter allows a cautious optimism that the objectives described in the project proposal will be materialized.

Following the project launching, project operations proceeded with of the study of open problems of contemporary wireless communications that interference alignment and massive MIMO can address. Timely investigation of all associated literature, allowed smooth interaction between work packages.

The strong interdisciplinary nature of interference alignment and massive MIMO dictates that research and development for each system should be performed in parallel. In this way, the proposed systems’ development minimize delays generated while investigating both techniques into interference management framework.

In terms of interference alignment, the research efforts focused on certain practical limitations, such as finite CSI feedback delay, which makes the knowledge of instantaneous perfect CSI impossible and brings the term of delayed CSIT to the forefront. Both current and delayed CSI have been exploited by generalizing the space-time interference alignment transmission algorithm (STIA) to the K (K ≥ 3) user M × N interference channel. In addition, we have investigated the degrees of freedom performance of the MIMO interference channel with limited channel state information feedback, and we have generalised two space-time interference alignment algorithms to the K user MIMO IC with a transmit power constraint. We have showed how these schemes exploit both current and outdated CSI to achieve an improved DoF performance. Nevertheless, we have studied the degrees of freedom of the two-user time-correlated MIMO interference channel, under realistic assumption, where the transmitters have imperfect knowledge of both the current and the delayed channel state information. The novelty of this study relies upon the fact that this is the first time, within the literature of interference channel, that imperfect CSI is addressed for such a case.

Regarding massive MIMO, we have considered a multi-cell multi-user downlink channel of a time-division duplex) MIMO system, where the base stations employ the concept of massive MIMO, i.e., they are equipped with a large number of antennas. In addition, the number of users increases with the same speed. Focusing on the practical impairments of the channel such as pilot contamination and, in particular, delayed channel state information at the transmitter (CSIT), we have derived an approximation of the sum rate with regularized zero-forcing (RZF) precoding, which provides a quantification of the capacity loss. For reasons of completeness, we have extended this analysis to the uplink channel by employ a MMSE decoder. Moreover, we have studied studies the uplink of a cellular network with zero-forcing receivers under imperfect channel state information at the base station. More specifically, apart from the pilot contamination, we investigate the effect of time variation of the channel due to the relative users’ movement with regard to the base station. Our contributions include analytical expressions for the sum-rate with finite number of BS antennas, and also the asymptotic limits with infinite power and number of BS antennas, respectively.

The goal is to develop new methods as well as integrate state-of-the-art methods in interference alignment and massive MIMO. Both concepts have emerged as new solutions to the interference problem. Especially, the latter one achieves to cancel out the inter-user and inter-cell interference. The anticipated solutions will be validated by simulations. The results will be published in prominent journals and conferences after being by reliable and respectful reviewers. The proposed approaches will establish new directions towards to more realistic systems that aim to be energy efficient and increase the throughput of the system.

Having completed the half-life of the project and advancing into the 2nd and final year provides us with a sufficient sample with respect to meeting the project’s objectives. The work performed since the beginning of the project has already led to a number of publications, ahead of the scheduled timeframe. The latter allows a cautious optimism that the objectives described in the project proposal will be materialized.

Following the project launching, project operations proceeded with of the study of open problems of contemporary wireless communications that interference alignment and massive MIMO can address. Timely investigation of all associated literature, allowed smooth interaction between work packages.

The strong interdisciplinary nature of interference alignment and massive MIMO dictates that research and development for each system should be performed in parallel. In this way, the proposed systems’ development minimize delays generated while investigating both techniques into interference management framework.

In terms of interference alignment, the research efforts focused on certain practical limitations, such as finite CSI feedback delay, which makes the knowledge of instantaneous perfect CSI impossible and brings the term of delayed CSIT to the forefront. Both current and delayed CSI have been exploited by generalizing the space-time interference alignment transmission algorithm (STIA) to the K (K ≥ 3) user M × N interference channel. In addition, we have investigated the degrees of freedom performance of the MIMO interference channel with limited channel state information feedback, and we have generalised two space-time interference alignment algorithms to the K user MIMO IC with a transmit power constraint. We have showed how these schemes exploit both current and outdated CSI to achieve an improved DoF performance. Nevertheless, we have studied the degrees of freedom of the two-user time-correlated MIMO interference channel, under realistic assumption, where the transmitters have imperfect knowledge of both the current and the delayed channel state information. The novelty of this study relies upon the fact that this is the first time, within the literature of interference channel, that imperfect CSI is addressed for such a case.

Regarding massive MIMO, we have considered a multi-cell multi-user downlink channel of a time-division duplex) MIMO system, where the base stations employ the concept of massive MIMO, i.e., they are equipped with a large number of antennas. In addition, the number of users increases with the same speed. Focusing on the practical impairments of the channel such as pilot contamination and, in particular, delayed channel state information at the transmitter (CSIT), we have derived an approximation of the sum rate with regularized zero-forcing (RZF) precoding, which provides a quantification of the capacity loss. For reasons of completeness, we have extended this analysis to the uplink channel by employ a MMSE decoder. Moreover, we have studied studies the uplink of a cellular network with zero-forcing receivers under imperfect channel state information at the base station. More specifically, apart from the pilot contamination, we investigate the effect of time variation of the channel due to the relative users’ movement with regard to the base station. Our contributions include analytical expressions for the sum-rate with finite number of BS antennas, and also the asymptotic limits with infinite power and number of BS antennas, respectively.

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Scientific Research**Record Number**: 184390 /

**Last updated on**: 2016-06-23