Digital Beamforming Structure Research Articles

Low complexity hybrid beamforming for downlink multi-user MIMO OFDM systems

Hybrid beamforming is critical for massive multiple input multiple output (MIMO) to achieve high spectral efficiency at reduced hardware cost. Existing hybrid beamforming schemes either design the analog beamforming and digital beamforming separately, or jointly optimize them through alternating optimization. Such strategies incur non-negligible performance degradation or huge computational complexity in optimization, which is especially evident with the partially connected architecture. In this work, we consider a general downlink multi-user MIMO orthogonal frequency division multiplexing (OFDM) system with the hybrid beamforming architecture, where finite-resolution phase shifters are adopted. We propose an efficient beamforming strategy on the sum rate maximization criterion. Rather than eliminating the interference entirely by digital beamforming, we optimize the analog beamforming by considering the interference at the same time. We consider a fixed digital beamforming structure to reduce the overall complexity. Given the fact of finite-resolution phase shifters, the analog beamforming is optimized over discrete phase values. Compared to existing hybrid beamforming designs, the proposed algorithm achieves much improved performance. By applying the average channel covariance to the analog beamforming design, the computational complexity of the proposed algorithm is further reduced. Meanwhile, the proposed algorithm is applicable to both fully and partially connected architectures.

Hybrid Multibeamforming Receiver With High-Precision Beam Steering for Low Earth Orbit Satellite Communication

A hybrid multibeamforming receiver for low Earth orbit (LEO) satellite communication in the Ku-band is designed and tested. The proposed receiver is implemented with eight channels to enable multibeam control. The proposed receiver, including both analog and digital beamforming structures, is capable of multibeam reception using both analog and digital beamforming techniques simultaneously or selectively. Analog beamforming is implemented by employing a local oscillator phase shifter using direct digital synthesis and phase-locked loop (PLL) structures. In digital beamforming, a software-defined radio can control the phase of the signal in the digital baseband. The multibeam received using the proposed hybrid multibeamforming receiver was measured at 11.7 GHz and 12.7 GHz in an anechoic chamber. The phase-control resolutions of analog and digital beamforming were 0.022° and 0.72°, respectively. Analog beam-switching speed is slower than digital beamforming because it depends on the settling time of the PLL circuit, but it has a high phase-control resolution. Therefore, by using analog and digital beamforming when precise beam tilting and fast beam switching are required, respectively, the proposed hybrid multibeamforming is shown to be suitable in accordance with the communication situation.

Beamforming Design for OFDM Joint Sensing and Communication System

<p>In this paper, we discussed the beamforming schemes for OFDM-based joint sensing and communication (OFDM-JSC) system, which enable JSC system to use directional beams to detect directions of interest, while communicating with one or more downlink users, thus further enhancing the practicability of JSC system. Specifically, we equip OFDM-JSC transmitter with hybrid beamforming structure and digital beamforming structure in SU-MIMO and MU-MISO scenarios, respectively. For SU-MIMO JSC, we separately considered the hybrid beamforming design with partially connected structure and fully connected structure. For MU-MISO JSC, we separately consider the beamforming design with total antenna array transmit power constraint, and per antenna transmit power constraint. For the four non-convex problems in above two scenarios, we have designed corresponding low-complexity JSC beamforming algorithms and we verified the effectiveness of proposed schemes through numerical simulation.</p> <p> </p>

A Simultaneous Wideband Calibration for Digital Beamforming Arrays at Short Distances [Measurements Corner

Massive multiple-input, multipleoutput (MIMO) is seen as an enabling technology for 5G communication systems [1]. Future base stations (BSs) featuring massive MIMO technology are expected to be equipped with a large number of antennas with digital beamforming structures, where the signals of all the channels are independently accessible. The array radiation pattern can be controlled via setting proper complex weights to the antenna elements to, e.g., form a beam in a desired direction to overcome the unfavorable propagation loss, or to form a null in an interference signal direction to suppress unwanted signals [2]. In addition, spatial multiplexing can also be utilized to serve multiple users simultaneously over the same time and frequency resource with various precoding schemes, which enlarges the network capacity.

Efficient Beamforming Training and Channel Estimation for Millimeter Wave OFDM Systems

We study the problem of downlink beamforming training and channel estimation for millimeter wave (mmWave) OFDM systems, where a hybrid analog and digital beamforming structure is employed at the transmitter (i.e., base station) and an omni-directional antenna or an antenna array is used at the receiver (i.e., user). To efficiently probe the channel, we form multiple directional beams simultaneously at the transmitter and steer them towards different directions. The objective is to devise the beam training sequence and develop an efficient algorithm to estimate the channel. By exploiting the sparse scattering nature of mmWave channels, the above problem is formulated as one of sparse encoding and signal recovery, which involves finding a sparse sensing matrix to compress the sparse channel and an efficient channel estimation algorithm to recover the sparse channel from compressive measurements. In this article, we propose a sparse bipartite graph code-based algorithm, where a set of bipartite graphs are employed to encode the sparse channel and a simple decoding procedure that relies on the presence of a No-Multiton-graph (NM-graph) is used to reconstruct the sparse channel. Theoretical analysis shows that our proposed method can help achieve a substantial training overhead reduction. Simulations are provided to show the effectiveness of the proposed algorithm and its performance advantage over compressed sensing-based methods.

Fast Beam Alignment for Millimeter Wave Communications: A Sparse Encoding and Phaseless Decoding Approach

In this paper, we studied the problem of beam alignment for millimeter wave (mmWave) communications, in which we assume a hybrid analog and digital beamforming structure is employed at the transmitter (i.e. base station), and an omni-directional antenna or an antenna array is used at the receiver (i.e. user). By exploiting the sparse scattering nature of mmWave channels, the beam alignment problem is formulated as a sparse encoding and phaseless decoding problem. More specifically, the problem of interest involves finding a sparse sensing matrix and an efficient recovery algorithm to recover the support and magnitude of the sparse signal from compressive phaseless measurements. A sparse bipartite graph coding (SBG-Coding) algorithm is developed for sparse encoding and phaseless decoding. Our theoretical analysis shows that, in the noiseless case, our proposed algorithm can perfectly recover the support and magnitude of the sparse signal with probability exceeding a pre-specified value from $\mathcal{O}(K^2)$ measurements, where $K$ is the number of nonzero entries of the sparse signal. The proposed algorithm has a simple decoding procedure which is computationally efficient and noise-robust. Simulation results show that our proposed method renders a reliable beam alignment in the low and moderate signal-to-noise ratio (SNR) regimes and presents a clear performance advantage over existing methods.

Low-Rank Tensor Decomposition-Aided Channel Estimation for Millimeter Wave MIMO-OFDM Systems

We consider the problem of downlink channel estimation for millimeter wave (mmWave) MIMO-OFDM systems, where both the base station (BS) and the mobile station (MS) employ large antenna arrays for directional precoding/beamforming. Hybrid analog and digital beamforming structures are employed in order to offer a compromise between hardware complexity and system performance. Different from most existing studies that are concerned with narrowband channels, we consider estimation of wideband mmWave channels with frequency selectivity, which is more appropriate for mmWave MIMO-OFDM systems. By exploiting the sparse scattering nature of mmWave channels, we propose a CANDECOMP/PARAFAC (CP) decomposition-based method for channel parameter estimation (including angles of arrival/departure, time delays, and fading coefficients). In our proposed method, the received signal at the BS is expressed as a third-order tensor. We show that the tensor has the form of a low-rank CP decomposition, and the channel parameters can be estimated from the associated factor matrices. Our analysis reveals that the uniqueness of the CP decomposition can be guaranteed even when the size of the tensor is small. Hence the proposed method has the potential to achieve substantial training overhead reduction. We also develop Cramer-Rao bound (CRB) results for channel parameters, and compare our proposed method with a compressed sensing-based method. Simulation results show that the proposed method attains mean square errors that are very close to their associated CRBs, and presents a clear advantage over the compressed sensing-based method in terms of both estimation accuracy and computational complexity.

Low complexity asymptotically unitary algorithm for hybrid beamforming in mmWave communication systems

In millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, because of the high hardware cost and high power consumption, the traditional fully digital beamforming (DBF) cannot be implemented easily. Meanwhile, analog beamforming which is implemented with phase shifters has high availability but suffers poor performance. Considering the advantages of above two, a potential solution is to design an appropriate hybrid analog and digital beamforming structure, where the available iterative optimization algorithm can get performance close to fully digital processing, but solving this sparse optimization problem faces with a high computational complexity. The key challenge of seeking out hybrid beamforming (HBF) matrices lies in leveraging the trade-off between the spectral efficiency performance and the computational complexity. In this paper, we propose an asymptotically unitary hybrid precoding (AUHP) algorithm based on antenna array response (AAR) properties to solve the HBF optimization problem. Firstly, we get the optimal orthogonal analog and digital beamforming matrices relying on the channel's path gain in absolute value by taking into account that the AAR matrices are asymptotically unitary. Then, an improved simultaneously orthogonal matching pursuit (SOMP) algorithm based on recursion is adopted to refine the hybrid combining. Numerical results demonstrate that our proposed AUHP algorithm enables a lower computational complexity with negligible spectral efficiency performance degradation.

Channel Estimation for Millimeter-Wave Multiuser MIMO Systems via PARAFAC Decomposition

We consider the problem of uplink channel estimation for millimeter wave (mmWave) systems, where the base station (BS) and mobile stations (MSs) are equipped with large antenna arrays to provide sufficient beamforming gain for outdoor wireless communications. Hybrid analog and digital beamforming structures are employed by both the BS and the MS due to hardware constraints. We propose a layered pilot transmission scheme and a CANDECOMP/PARAFAC (CP) decomposition-based method for joint estimation of the channels from multiple users (i.e., MSs) to the BS. The proposed method exploits the intrinsic low-rank structure of the multiway data collected from multiple modes, where the low-rank structure is a result of the sparse scattering nature of the mmWave channel. The uniqueness of the CP decomposition is studied, and the sufficient conditions for essential uniqueness are obtained. The conditions shed light on the design of the beamforming matrix, the combining matrix, and the pilot sequences, and meanwhile provide general guidelines for choosing system parameters. Our analysis reveals that our proposed method can achieve a substantial training overhead reduction by leveraging the low-rank structure of the received signal. Simulation results show that the proposed method presents a clear advantage over a compressed sensing-based method in terms of both estimation accuracy and computational complexity.

Large-scale antenna systems with hybrid analog and digital beamforming for millimeter wave 5G

With the severe spectrum shortage in conventional cellular bands, large-scale antenna systems in the mmWave bands can potentially help to meet the anticipated demands of mobile traffic in the 5G era. There are many challenging issues, however, regarding the implementation of digital beamforming in large-scale antenna systems: complexity, energy consumption, and cost. In a practical large-scale antenna deployment, hybrid analog and digital beamforming structures can be important alternative choices. In this article, optimal designs of hybrid beamforming structures are investigated, with the focus on an N (the number of transceivers) by M (the number of active antennas per transceiver) hybrid beamforming structure. Optimal analog and digital beamforming designs in a multi-user beamforming scenario are discussed. Also, the energy efficiency and spectrum efficiency of the N × M beamforming structure are analyzed, including their relationship at the green point (i.e., the point with the highest energy efficiency) on the energy efficiency-spectrum efficiency curve, the impact of N on the energy efficiency performance at a given spectrum efficiency value, and the impact of N on the green point energy efficiency. These results can be conveniently utilized to guide practical LSAS design for optimal energy/ spectrum efficiency trade-off. Finally, a reference signal design for the hybrid beamform structure is presented, which achieves better channel estimation performance than the method solely based on analog beamforming. It is expected that large-scale antenna systems with hybrid beamforming structures in the mmWave band can play an important role in 5G.

Hybrid phase-shift/time-delay digital beamforming

Digital phase-shift beamforming of narrow-band signals from uniform colinear hydrophone arrays may be accomplished by computationally efficient algorithms which exploit the functional regularity of the required phase-shift operations. However, phase-shift beamforming is a valid approximation to delay-and-sum steering over only a limited bandwidth whose value depends on array aperture and steering angle. This paper describes a multiple-beam digital beamforming structure which is a phase-shift/time-delay hybrid and which an be designed for operating bandwidths in excess of the phase-shift limit. Much of the computational efficiency of colinear array phase-shift beamforming is retained in this approach, and it can offer substantial advantage over the alternative of delay steering by digital interpolation. This will be demonstrated by examples.