In the last decades the world has experienced a massive growth in the demand for wireless services. The recent popularity of hand-held devices with data exchange capabilities over wireless networks, such as smartphones and tablets, increased the wireless data traffic even further. This trend is not expected to cease in the foreseeable future. In fact, it is expected to accelerate as everyday apparatus unrelated with data communications, such as vehicles or household devices, are foreseen to be equipped with wireless communication capabilities.
Further, the next generation wireless networks should be designed such that they have increased spectral and energy efficiency, provide uniformly good service to all of the accommodated users and handle many more devices simultaneously. Massive multiple-input multiple-output (Massive MIMO) systems, also termed as large-scale MIMO, very large MIMO or full-dimension MIMO, have recently been proposed as a candidate technology for next generation wireless networks. In Massive MIMO, base stations (BSs) with a large number of antenna elements serve simultaneously only a few tens of single antenna, non-cooperative users. As the number of BS antennas grow large, the normalized channel vectors to the users become pairwise asymptotically orthogonal and, therefore, simple linear processing techniques are optimal. This is substantially different from the current design of contemporary cellular systems, where BSs are equipped with a few antennas and the optimal processing is complex. Consequently, the need for redesign of the communication protocols is apparent.
The deployment of Massive MIMO requires the use of many inexpensive and, potentially, off-the-shelf hardware components. Such components are likely to be of low quality and to introduce distortions to the information signal. Hence, Massive MIMO must be robust against the distortions introduced by the hardware impairments. Among the most important hardware impairments is phase noise, which is introduced by local oscillators (LOs) at the BS and the user terminals. Phase noise is a phenomenon of particular importance since it acts multiplicatively on the desired signal and rotates it by some random and unknown argument. Further, the promised gains of Massive MIMO can be reaped by coherent combination of estimated channel impulse responses at the BS antennas. Phase noise degrades the quality of the estimated channel impulse responses and impedes the coherent combination of the received waveforms.
In this dissertation, wideband transmission schemes and the effect of phase noise on Massive MIMO are studied. First, the use of a low-complexity single-carrier precoding scheme for the broadcast channel is investigated when the number of BS antennas is much larger than the number of served users. A rigorous, closed-form lower bound on the achievable sum-rate is derived and a scaling law on the potential radiated energy savings is stated. Further, the performance of the proposed scheme is compared with a sum-capacity upper bound and with a bound on the performance of the contemporary multi-carrier orthogonal frequency division multiplexing (OFDM) transmission.
Second, the effect of phase noise on the achievable rate performance of a wideband Massive MIMO uplink with time-reversal maximum ratio combining (TRMRC) receive processing is investigated. A rigorous lower bound on the achievable sum-rate is derived and a scaling law on the radiated energy efficiency is established. Two distinct LO configurations at the BS, i.e., the common LO (synchronous) operation and the independent LO (non-synchronous) operation, are analyzed and compared. It is concluded that the non-synchronous operation is preferable due to an averaging of the independent phase noise sources. Further, a progressive degradation of the achievable rate due to phase noise is observed. A similar study is extended to a flat fading uplink with zero-forcing (ZF) receiver at the BS.
The fundamental limits of data detection in a phase-noise-impaired uplink are also studied, when the channel impulse responses are estimated via uplink training. The corresponding maximum likelihood (ML) detector is provided for the synchronous and non-synchronous operations and for a general parameterization of the phase noise statistics. The symbol error rate (SER) performance at the high signal-to-noise ratio (SNR) of the detectors is studied. Finally, rigorous lower bounds on the achievable rate of a Massive MIMO-OFDM uplink are derived and scaling laws on the radiated energy efficiency are stated.
Linköping: Linköping University Electronic Press, 2016. , 57 p.