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  • 1.
    Celebi, Hasan Basri
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Pitarokoilis, Antonios
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Training-assisted channel estimation for low-complexity squared-envelope receivers2018In: 2018 IEEE 19TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), IEEE , 2018, p. 196-200Conference paper (Refereed)
    Abstract [en]

    Squared-envelope receivers, also known as energy detectors, are, due to their simplified circuitry, low-cost and low-complexity receivers. Hence they are attractive implementation structures for future Internet-of-Things (IoT) applications. Even though there is considerable work on the wider research area of squared-envelope receivers, a comprehensive comparison and statistical characterization of training-assisted channel estimators for squared-envelope receivers appear to be absent from the literature. A detailed description of practical channel estimation schemes is necessary for the optimal training design of latency-constrained IoT applications. In this paper, various channel estimators are derived, their bias and variance are studied, and their performance is numerically compared against the Cramer-Rao lower bound.

  • 2.
    Celebi, Hasan Basri
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Pitarokoilis, Antonios
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Training-Assisted Channel Estimation for Low-Complexity Squared-Envelope Receivers2018In: IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, Institute of Electrical and Electronics Engineers Inc. , 2018Conference paper (Refereed)
    Abstract [en]

    Squared-envelope receivers, also known as energy detectors, are, due to their simplified circuitry, low-cost and low-complexity receivers. Hence they are attractive implementation structures for future Internet-of-Things (IoT) applications. Even though there is considerable work on the wider research area of squared-envelope receivers, a comprehensive comparison and statistical characterization of training-assisted channel estimators for squared-envelope receivers appear to be absent from the literature. A detailed description of practical channel estimation schemes is necessary for the optimal training design of latency-constrained IoT applications. In this paper, various channel estimators are derived, their bias and variance are studied, and their performance is numerically compared against the Cramer-Rao lower bound.

  • 3.
    Pitarokoilis, Antonios
    et al.
    KTH, School of Electrical Engineering (EES), Information Science and Engineering. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Bjomson, E.
    Larsson, E. G.
    On the effect of imperfect timing synchronization on pilot contamination2017In: 2017 IEEE International Conference on Communications, ICC 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 7996671Conference paper (Refereed)
    Abstract [en]

    The phenomenon of pilot contamination (PC) in multi-cell Massive MIMO systems is investigated in the presence of imperfect timing synchronization (TS). In particular, a basic setup is considered, where a base station (BS) is perfectly synchronized with the user of its cell, but there is imperfect TS between the BS and the user in another cell, possibly due to different propagation distances. A discrete-time system model is derived based on the continuous-time system model. The discrete-time system model accurately captures the phenomenon of imperfect TS in terms of the timing mismatch and the pulse shaping filter impulse responses. The derived discrete-time system model is used to study the achievable rates of a two-cell Massive MIMO uplink. It is shown that the structure imposed to the pilot contaminating signal due to the imperfect TS can be leveraged to mitigate the effect of PC. The level of PC suppression is quantified as a function of the timing mismatch and the characteristics of the transmit/receive pulse shaping filters.

  • 4.
    Pitarokoilis, Antonios
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Gross, James
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Ultra-Reliable Low-Latency Communication of Periodic and Event-Triggered Dependable Traffic Streams2018In: Proceedings of the International Symposium on Wireless Communication Systems, VDE Verlag GmbH , 2018Conference paper (Refereed)
    Abstract [en]

    The efficient design of ultra-reliable low-latency communication (URLLC) is a major research objective for next generation wireless systems, in particular for industrial automation applications. Massive MINO has been successful in providing high spectral and energy efficiency, and it is of importance to investigate the potential gains and limitations it exhibits when applied for URLLC. We study a scenario where two sets of nodes with different traffic characteristics communicate with a central node equipped with multiple antenna elements. We characterize the outage probability when fully orthogonal training sequences are used versus sharing of the training sequences between the two sets of nodes. It is shown that substantial performance gains can be reaped with shared training sequences when there are strict latency requirements and/or large number of nodes to be served.

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