A Receiver Architecture For Dual-Functional Massive MIMO OFDM RadCom Systems

This study introduces a receiver architecture for dual-functional communication and radar (RadCom) base-stations (BS), which exploits the spatial diversity between the received radar and communication signals, and performs interference cancellation (IC) to successfully separate these signals. In the RadCom system under consideration, both communication and radar systems employ orthogonal frequency-division multiplexing (OFDM) waveforms with overlapping subcarriers. Employing OFDM waveform allows the BS to simultaneously perform uplink channel estimation on the narrow-band subcarriers to efficiently obtain full channel state information (CSI) between the users (UEs) and the BS antenna elements. The estimated CSI matrix is then utilized to acquire uplink data streams from the UEs by suppressing the inter-user interference and radar signals which arrive at the BS through unknown channels. After acquiring the UEs' data, radar signals are extracted from the received complex baseband signals by performing interference cancellation. The proposed method has been analyzed mathematically and verified by simulations under various conditions including CSI mismatch and high radar interference. The results show that 16QAM modulated uplink is outstandingly robust against radar interference and that having a large number of antennas significantly improves the performance of both communication and radar subsystems, cooperatively. This study shows that it is possible to distinguish radar and communication signals by employing large-scale antenna arrays to successfully realize a RadCom receiver for future communication networks

On the Impact of Antenna Array Geometry on Indoor Wideband Massive MIMO Networks

Multi-user massive multiple-input-multiple-output (massive MIMO) will play a key role in future wireless communication networks. Since spatial channel diversity is the fundamental merit of this technique, high channel correlation may significantly restrict its abilities. This study investigates the impact of channel correlation on a prototyped massive MIMO network with the objective to identify an antenna array geometry which has reduced mutual coupling and channel correlation. To this end, a highly efficient directional wideband single antenna element was designed for the antenna arrays and the user equipments (UEs). The designed array geometry is tested in an experimental indoor wideband massive MIMO setup. Important system parameters, such as channel correlation, power delay profile, and average received power from the UEs, are studied by analyzing the measured channel data. Furthermore, system-level simulations and network capacity calculations are performed based on the measured channel data to evaluate the performance of the prototyped antenna arrays. A regular array was also fabricated and used for benchmarking comparison. Moreover, a power control algorithm is introduced for the uplink, which was shown to improve the network capacity by up to 3 dB. The results demonstrate that the introduced antenna array outperforms the uniform antenna array in terms of mutual coupling and channel capacity

Simplified Formulae for the Estimation of Offshore Wind Turbines Clutter on Marine Radars

The potential impact that offshore wind farms may cause on nearby marine radars should be considered before the wind farm is installed. Strong radar echoes from the turbines may degrade radars' detection capability in the area around the wind farm. Although conventional computational methods provide accurate results of scattering by wind turbines, they are not directly implementable in software tools that can be used to conduct the impact studies. This paper proposes a simple model to assess the clutter that wind turbines may generate on marine radars. This method can be easily implemented in the system modeling software tools for the impact analysis of a wind farm in a real scenario

Impact of imperfect channel estimation and antenna correlation on quantised massive multiple-input multiple-output systems

This study examines the uplink performance of large-constellation multi-user massive multiple-input multiple-output systems with low-resolution analogue-to-digital converters (ADCs) in the presence of channel correlation and imperfect channel state information (CSI). The base station (BS) employs a large number of antennas for multiplexing and demultiplexing co-channel users with each antenna element having a dedicated radio frequency chain and two low-resolution ADCs. While such ADCs cause data loss due to coarse quantisation, the large number of antennas can be exploited not only to alleviate such a problem but also to make it possible to utilise large-constellation modulation schemes. The results provide an insight into the trade-off between various performance metrics and the number of quantisation bits under a wide range of realistic conditions. It will be shown that 1-bit quantisation provides sufficient resolution with 100 BS antennas to communicate with ten user equipments using quadrature phase shift keying, but the number of quantisation bits must be increased for larger constellations particularly to overcome CSI mismatch and channel correlation. The results also consider the trade-off between average mutual information and power consumption of the low-resolution ADCs. It will be shown that 16-quantum amplitude modulation with 2-bit quantisation may provide a good compromise between energy efficiency and average mutual information