Millimetre-wave (mmWave) communications have been regarded as a key technology for the next-generation cellular systems since the huge available bandwidth can potentially provide the rates of multiple gigabits per sec...
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Millimetre-wave (mmWave) communications have been regarded as a key technology for the next-generation cellular systems since the huge available bandwidth can potentially provide the rates of multiple gigabits per second. Conventional precoding and combining techniques are impractical at mmWave scenarios due to manufacturing costs and power consumption. hybrid alternatives have been considered as a promising technology to provide a compromise between hardware complexity and system performance. This study examines, using a semi-analytic approach, the downlink performance of massive MU-MIMO mmWave systems in terms of the bit error rate (BER). Also, a general expression is derived to estimate an upper bound/approximation to the BER performance via the Monte Carlo method, which can be used for any hybridprecoder/combiner, modulation and different data detectors. Numerical results evidence that the approximate BER expressions provide values very close to the ones obtained through simulation using only two statistical moments related to parameters of the system, mean and variance.
hybrid analog and digital precoding allows millimeter wave (mmWave) systems to achieve both array and multiplexing gain. The design of the hybridprecoders and combiners, though, is usually based on the knowledge of t...
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hybrid analog and digital precoding allows millimeter wave (mmWave) systems to achieve both array and multiplexing gain. The design of the hybridprecoders and combiners, though, is usually based on the knowledge of the channel. Prior work on mmWave channel estimation with hybrid architectures focused on narrowband channels. Since mmWave systems will be wideband with frequency selectivity, it is vital to develop channel estimation solutions for hybrid architectures-based wideband mmWave systems. In this paper, we develop a sparse formulation and compressed sensing-based solutions for the wideband mmWave channel estimation problem for hybrid architectures. First, we leverage the sparse structure of the frequency-selective mmWave channels and formulate the channel estimation problem as a sparse recovery in both time and frequency domains. Then, we propose explicit channel estimation techniques for purely time or frequency domains and for combined time/frequency domains. Our solutions are suitable for both single carrier-frequency domain equalization and orthogonal frequency-division multiplexing systems. Simulation results show that the proposed solutions achieve good channel estimation quality, while requiring small training overhead. Leveraging the hybrid architecture at the transceivers gives further improvement in estimation error performance and achievable rates.
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