# Advanced Noncoherent Detection in Massive MIMO Systems via Digital Beamspace Preprocessing
## 1 Introduction  
The massive multiple-input/multiple-output (MIMO) technology embodies one of the key elements in future wireless communication systems [1; 2; 3; 4; 5; 6]. Equipped with a very large number of antennas at the base station (BS), massive MIMO systems offer the potential to meet the ever-increasing demand for high throughput and energy efficiency. To this end, sufficiently accurate channel state information (CSI) is essential, which is gathered via pilot signaling using predefined (orthogonal) pilot symbols. Since the number of channel coefficients to be estimated is huge in massive MIMO systems, CSI acquisition can become a challenging task and may suffer from pilot contamination due the re-use of pilot symbols in neighboring communication cells [7]. Moreover, outdated CSI or estimation inaccuracies have a severe impact on the system performance [8; 9]. Additionally, the channel-training overhead reduces the overall time, where data can be transmitted resulting in a loss of spectral efficiency [10]. In order to overcome the need of channel estimation and pilot symbol allocation, noncoherent detection schemes can be applied in the uplink as proposed in [11; 12]. Here, actual channel knowledge is not required to recover the individual transmitted data streams but the per-user induced power over the receive antennas of the BS, namely the user-specific power-space profile (PSP) of the users. As long as the users can be separated at the BS in terms of their spatially induced power, noncoherent detection performs comparably to its CSI-based (coherent) counterpart [13; 14]. However, the spatial separation can only be obtained in scenarios where the users are located in thenear-field of a physically-large BS [15, 16, 17, 18]. Consequently an adaption is needed to handle far-field users and to keep the overall size of the BS in an acceptable range for a practical implementation. To this end, (analog) beamspace techniques can be employed focusing the energy of the incoming waves to a smaller subset of the BS antenna array depending on the angle of arrival. This process can also be interpreted as a spatial Fourier transform. Exploiting the angular sparsity of the propagation channel, where the uplink transmit signals of the users impinge at the BS from sufficiently different angular directions, the users can be separated enabling again the noncoherent detection scheme. This has been successively demonstrated for a lens-embedded and an analog beamforming-based system [19, 20]. So far, lens antenna arrays were investigated solely in the context of coherent massive MIMO transceivers aiming at a reduction of hardware costs in both uplink and downlink [21, 22, 23, 24, 25, 26]. The same applies to the studies in [27, 28, 29, 30, 31], where an alternative representation of the lens is used on the concept of beamspace MIMO. To achieve the crucial user separation for noncoherent detection in far-field scenarios, the proposed analog beamspace techniques in [19, 20] require additional bulky hardware, which can suffer from non-idealities, high complexity, and lacking adaptability to specific channel conditions. Thus, an all digital implementation is of major interest avoiding the stated issues and providing the potential of even improved user separability via adapted signal processing at the same time. This work studies beamspace techniques in the digital domain and its application to the noncoherent detection scheme. To this end, the relevant requirements are identified and detailed to conceive a highly advanced and competitive noncoherent detection scheme compared to the classical and initial approach proposed in [11, 12] by means of digital beamspace preprocessing. Originally, a high-quality phase reference and a perfect synchronization of the local oscillators (LOs) is not required in case of noncoherent detection. Consequently it can benefit from a low-complexity LO distribution network, where independent LOs for each receive branch can be employed for instance [17].