Multi-Cell Hybrid Millimeter Wave Systems: Pilot Contamination and Interference Mitigation

Abstract

In this paper, we investigate the system performance of a multi-cell multi-user (MU) hybrid millimeter wave (mmWave) communications in a multiple-input multiple-output (MIMO) network. Due to the reuse of pilot symbols among different cells, the performance of channel estimation is expected to be degraded by pilot contamination, which is considered as a fundamental performance bottleneck of conventional multicell MU massive MIMO networks. To analyze the impact of pilot contamination to the system performance, we first derive the closed-form approximation of the normalized mean squared error (MSE) of the channel estimation algorithm proposed in [2] over Rician fading channels. Our analytical and simulation results show that the channel estimation error incurred by the impact of pilot contamination and noise vanishes asymptotically with an increasing number of antennas equipped at each radio frequency (RF) chain at the desired BS. Furthermore, by adopting zero-forcing (ZF) precoding in each cell for downlink transmission, we derive a tight closed-form approximation of the average achievable rate per user. Our results unveil that the intra-cell interference and inter-cell interference caused by pilot contamination over Rician fading channels can be mitigated effectively by simply increasing the number of antennas equipped at the desired BS.

Low-Complexity Multiuser Receiver for Massive Hybrid Array mmWave Communications

“…We assume that each user equipped with eight antennas can estimate its AoA in LOS directions and configure the corresponding BF vector perfectly in Step 1. Each user's signal experiences multipath fading, where the number of multipath is 8 with one dominating LOS-path and 7 NLOS-paths [12], [29]. The AoAs of all users' signals at both the BS and users sides are uniformly distributed in the range [−π/2, π/2].…”

Interference Management in 5G and Beyond Network: Requirements, Challenges and Future Directions

“…Pilot sequence division in chain network [199,200], large scale fading precoding [201], zero-forcing (ZF) precoding [202] Non-ideal transceiver hardware [203], I/Q imbalance [204], transceiver impairment in multi-user multi-cell [205], oscillator phase noise [206], transmitter branches distortion noise [207], non-reciprocal transceiver [208], pilot sequence in-band FD M-MIMO [209] Unmanned aerial vehicles Echo state network [210], analysis of interference in UAV [211], power control and coverage extension for uplink (UL)-downlink (DL) [212], impact of UL interference [213], multi-beam UAV UL [214], ICIC design UAV UL [215], cooperative NOMA [216] Downstream interference issues in different scenarios of cellular users and UAVs…”

“…The interference effect in a signal decreases the achievable rates and overall efficiency of the spectrum. Extensive literature work dedicated to eliminating ICI with a primary focus on reducing pilot symbol contamination in channel estimation [200][201][202]. These techniques have helped reduce the bit error rate (BER) issue and enhance a spectrum's efficiency.…”

Distributed Estimation Framework for Beyond 5G Intelligent Vehicular Networks

“…Wireless communication is the key enabler for realizing the potentials of IVN in the future B5G wireless networks. In particular, millimeter wave (mmWave) communication [127]- [129] has been widely recognized as an enabling technology to meet the needs of data-intensive applications in future in-vehicle infotainment systems. Besides, the abundant spectrum in the mmWave frequency band can be exploited for accurate localization and tracking of vehicle.…”