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  • 1.
    Alodeh, Maha
    et al.
    Univ Luxembourg, Luxembourg.
    Spano, Danilo
    Univ Luxembourg, Luxembourg.
    Kalantari, Ashkan
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten. Univ Luxembourg, Luxembourg.
    Tsinos, Christos G.
    Univ Luxembourg, Luxembourg.
    Christopoulos, Dimitrios
    Newtec Satcom, Belgium.
    Chatzinotas, Symeon
    Univ Luxembourg, Luxembourg.
    Ottersten, Bjorn
    Univ Luxembourg, Luxembourg.
    Symbol-Level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-Art, Classification, and Challenges2018Inngår i: IEEE Communications Surveys and Tutorials, E-ISSN 1553-877X, Vol. 20, nr 3, s. 1733-1757Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Precoding has been conventionally considered as an effective means of mitigating or exploiting the interference in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: 1) transmitting distinct data streams to groups of users and 2) applying precoding on a symbol-persymbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: 1) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding and 2) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area.(1)

  • 2.
    Tsinos, Christos G.
    et al.
    Univ Luxembourg, Luxembourg.
    Kalantari, Ashkan
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    Chatzinotas, Symeon
    Univ Luxembourg, Luxembourg.
    Ottersten, Bjorn
    Univ Luxembourg, Luxembourg.
    Symbol-Level Precoding with Low Resolution DACs for Large-Scale Array MU-MIMO Systems2018Inngår i: 2018 IEEE 19TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), IEEE , 2018, s. 671-675Konferansepaper (Fagfellevurdert)
    Abstract [en]

    While (Multiple Input-Multiple Output) MIMO systems based on large-scale antenna arrays are seen as the solution to the continuously increasing demands in modern wireless systems, they require high hardware complexity and power consumption. To tackle this, solutions based on low resolution Analog-to-Digital Converters (ADCs) / Digital-to-Analog Converters (DACs) have been developed in the literature where they mainly propose quantized versions of typical channel dependent linear precoding solutions. Alternatively, nonlinear Symbol level Precoding techniques have been recently proposed for downlink Multi User (MU)-MIMO systems with low resolution DACs that achieve significantly improved performance in several cases. The existing SLP approaches support only DACs of 1-bit resolution which result in significant performance degradations, especially when constellations with order greater than 4 are employed. To that end, in this work a novel SLP approach is developed that supports systems with DACs of any resolution and it is applicable for any type of constellation. As it is verified by the presented numerical results, the proposed approach exhibits significantly improved performance when constellations with order greater than 4 are employed and require reduced computational complexity, compared to the existing solutions for the 1-bit DAC case.

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