Beam Division Multiple Access Research Articles

Cluster-Based Multi-Carrier Hybrid Beamforming for Massive Device Terahertz Communications

We propose a cluster-based multi-carrier beam division multiple access (MC-BDMA) scheme to enable massive device terahertz (THz) communications with the dynamic-subarray hybrid beamforming (HBF) architecture. This scheme is motivated by a limitation of conventional HBF architectures, i.e., the number of users cannot exceed the number of radio frequency (RF) chains. By exploiting the unique properties of THz channels, such as high distance-and-frequency dependence, high sparsity, and small angular spread, we propose multiple users in the same cluster to be supported by a single RF chain with distance-aware multi-carrier modulation. Moreover, we propose different clusters to be divided by BDMA that is accomplished through HBF design. In our proposed scheme, we first design a novel antenna selection and subarray partition algorithm for the dynamic-subarray HBF architecture to compensate for performance loss caused by diverse channels among users. We then design an algorithm for multi-carrier HBF which maximizes the achievable throughput and eliminates the inter-beam interference. Numerical results show that our proposed cluster-based MC-BDMA scheme with the dynamic-subarray HBF architecture provides an almost 100% spectral efficiency gain and a 60% energy efficiency gain over the conventional non-cluster HBF scheme in massive device communications.

FUNDAMENTALS OF 5G TECHNOLOGY FOR NEXT GENERATION NETWORKS

5G architecture using nanocore involve the technologies such as cloud computing, nanotechnology, and All IP network. Multiple Access technologies like CDMA, OFDMA, TDMA and FDMA are defined. By increasing the capacity of the system BDMA (Beam Division Multiple Access) technique allows multiple access to Mobile Station (MS). Beam Division Multiple Access (BDMA) transference or transmission provides concurrently numerous users completely over the discrete beams. By organizing out users within the non-overlapping beams, the MU-Multiple input Multiple output channels can be uniformly decay into multiple single-user and Multiple input Multiple output (MIMO) channels; this method significantly reduce above channel estimation method, as well as the processing complexity at transmitters and receivers. Keywords- MIMO, BDMA, nanocore, AIP

Beam division multiple access for millimeter wave massive MIMO: Hybrid zero-forcing beamforming with user selection

<p>Massive multiple-input multiple-output (MIMO) systems are considered a promising solution to minimize multiuser interference (MUI) based on simple precoding techniques with a massive antenna array at a base station (BS). This paper presents a novel approach of beam division multiple access (BDMA) which BS transmit signals to multiusers at the same time via different beams based on hybrid beamforming and user-beam schedule. With the selection of users whose steering vectors are orthogonal to each other, interference between users is significantly improved. While, the efficiency spectrum of proposed scheme reaches to the performance of fully digital solutions, the multiuser interference is considerably reduced.</p>

Hybrid precoding for cluster-based multi-carrier beam division multiple access in terahertz wireless communications

Terahertz (THz) wireless communication has the capability to connect massive devices using its ultra-large spectrum resource. We propose a hybrid precoding scheme for the cluster-based multi-carrier beam division multiple access (MC-BDMA) to enable THz massive connections. Both the inter-beam interference and inter-band power leakage in this system are considered. A mathematical model is established to analyze and reduce their effects on the THz signal transmission. By considering the peculiarities of THz channels and characteristics of THz hardware components, we further propose a three-step hybrid precoding algorithm with low complexity, where the received signal power enhancement, the inter-beam interference elimination, and the inter-band power leakage suppression are conducted in succession. Simulation results are presented to demonstrate the high spectrum efficiency and high energy efficiency of our proposed algorithm, especially in the massive-connection scenarios.

Beam Selection Assisted UAV‐BS Deployment and Trajectory for Beamspace mmWave Systems

Exploiting unmanned aerial vehicles (UAVs) as base stations (UAV‐BS) can enhance capacity, coverage, and energy efficiency of wireless communication networks. To fully realize this potential, millimeter wave (mmWave) technology can be exploited with UAV‐BS to form mmWave UAV‐BS. The major difficulty of mmWave UAV‐BS, however, lies in the limited energy of UAV‐BS and the multiuser interference (MUI). Beam division multiple access with orthogonal beams can be employed to alleviate the MUI. Since each user has dominant beams around the line of sight direction, beam selection can reduce the power consumption of radio frequency chain. In this paper, we formulate the problem of maximizing the sum rate of all users by optimizing the beam selection for beamspace and UAV‐BS deployment in the mmWave UAV‐BS system. This nonconvex problem is solved in two steps. First, we propose a signal‐to‐interference plus noise ratio‐based greedy beam selection scheme to ensure that all the ground users in the given area can be served by the UAV‐BS, where a zero forcing precoding scheme is used to eliminate the MUI. Then, we utilize the continuous genetic algorithm to find the optimal UAV‐BS deployment and beam pattern to maximize the sum rate of all users. Moreover, considering the mobility of the UAV‐BS, the UAV‐BS trajectory and beam selection for beamspace are optimized in the mmWave UAV‐BS system. The simulation results demonstrate the effectiveness of the proposed design for the mmWave UAV‐BS system.

Learning to Compute Ergodic Rate for Multi-Cell Scheduling in Massive MIMO

In this article, we investigate multi-cell scheduling for massive multiple-input-multiple-output (MIMO) communications with only statistical channel state information (CSI). The objective of multi-cell scheduling is to activate a subset of users so as to maximize the ergodic sum rate subject to per-cell total transmit power constraint. By adopting beam division multiple access based on the statistical CSI, i.e., channel-coupling matrix (CCM), we simplify multi-cell scheduling as a power control problem in the beam domain, by which the ergodic sum rate is maximized. To reduce the computational burden on finding the ergodic sum rate, we propose a learning-to-compute strategy, which directly computes the complex ergodic rate function from CCMs via a deep neural network. Specifically, by modeling the probability density function of the ordered eigenvalues of the Hermitian CCM matrices as exponential family distributions, a properly designed hybrid neural network makes the ergodic rate computation feasible. With the learning-to-compute strategy, the online computational complexity of multi-cell scheduling is substantially reduced compared with the existing Monte Carlo or deterministic equivalent (DE) based methods while maintaining nearly the same performance.

Block Diagonal Hybrid Precoding and Power Allocation for QoS-Aware BDMA Downlink Transmissions.

Beam Division Multiple Access (BDMA) with hybrid precoding has recently been proposed for multi-user multiple-input multiple-output (MU-MIMO) systems by simultaneously transmitting multiple digitally precoded users’ data-streams via different beams. In contrast to most existing works that assume the number of radio frequency (RF) chains must be greater than or equal to that of data-streams, this work proposes a novel BDMA downlink system by first grouping transmitting data-streams before digitally precoding data group by group. To fully harvest the benefits of this new architecture, a greedy user grouping algorithm is devised to minimize the inter-group interference while two digital precoding approaches are developed to suppress the intra-group interference by maximizing the signal-to-interference-and-noise ratio (SINR) and the signal-to-leakage-and-noise ratio (SLNR), respectively. As a result, the proposed BDMA system requires less RF chains than the total number of transmit data-streams. Furthermore, we optimize the power allocation to satisfy each user’s quality of service (QoS) requirement using the D.C. (difference of convex functions) programming technique. Simulation results confirm the effectiveness of the proposed scheme.

Networked Optical Massive MIMO Communications

The low cost and versatility of optical devices make it possible to pack a large number of optical transceivers into arrays and exploit massive multiple-input multiple-output (MIMO) transmission in optical wireless communications. Nevertheless, optical massive MIMO presents several distinct challenges such as, the line-of-sight propagation and intensity modulation, incompatible with existing radio frequency massive MIMO techniques. This paper presents a networked optical massive MIMO system that consists of multiple base stations (BSs), each equipped with a transmit lens and an optical transmitter array, cooperatively serving a number of user terminals (UTs), each equipped with a receive lens and a photodetector array. We establish the optical massive MIMO channel model, analyze its asymptotic behavior, and evaluate the potential of networked optical massive MIMO on system throughput improvement. To achieve high throughput, we propose optical beam division multiple access (BDMA) transmission schemes under the total and per transmitter power constraints with the asymptotic optimality. Our results show that the system sum rate increases proportionally to the number of BSs and UTs using the optical BDMA transmission. Further numerical results show that the proposed optical massive MIMO system along with the optical BDMA transmission is able to achieve high throughput with low complexity.

Massive Beam-Division Multiple Access for B5G Cellular Internet of Things

In this article, we investigate the issue of massive access in a beyond fifth-generation (B5G) cellular Internet of Things (IoT) network. To reduce the overhead of channel state information acquisition and the complexity of transceiver design, an integrated framework of massive beam-division multiple access (BDMA) is proposed according to the characteristics of beamspace propagation. Then, we analyze the performance of the proposed massive BDMA scheme and derive a closed-form expression for the weighted sum rate in terms of channel conditions and system parameters. To improve the overall performance, we propose a massive access algorithm by jointly optimizing transmit power and receive vector. It is found that the optimal receive vector for each IoT device is the base beam corresponding to the arrival of angle of the IoT device’s signal in the beamspace, which significantly simplifies the design of the receiver. Considering the constraint of radio-frequency (RF) chains in practical networks, we propose a clustering-based massive access algorithm, which allocates an RF chain for a cluster. Finally, extensive simulation results confirm that the proposed algorithms can provide small overhead and low complexity massive access schemes for B5G cellular IoT.

Beam Domain Massive MIMO for Optical Wireless Communications With Transmit Lens

This paper presents a novel massive multiple-input multiple-output (MIMO) transmission in beam domain for optical wireless communications. The optical base station equipped with massive optical transmitters communicates with a number of user terminals (UTs) through a transmit lens. Focusing on LED transmitters, we analyze light refraction of the lens and establish a channel model for optical massive MIMO transmissions. For a large number of LEDs, channel vectors of different UTs become asymptotically orthogonal. We investigate the maximum ratio transmission and regularized zero-forcing precoding in the optical massive MIMO system, and propose a linear precoding design to maximize the sum rate. We further design the precoding when the number of transmitters grows asymptotically large, and show that beam division multiple access (BDMA) transmission achieves the asymptotically optimal performance for sum rate maximization. Unlike optical MIMO without a transmit lens, BDMA can increase the sum rate proportionally to $2K$ and $K$ under the total and per transmitter power constraints, respectively, where $K$ is the number of UTs. In the non-asymptotic case, we prove the orthogonality conditions of the optimal power allocation in beam domain and propose efficient beam allocation algorithms. Numerical results confirm the significantly improved performance of our proposed beam domain optical massive MIMO communication approaches.

Multiple Access MmWave Design for UAV-Aided 5G Communications

Unmanned aerial vehicles (UAVs) have tremendous potential to improve wireless network capacity, but are challenging to operate in ultra-dense networks, mainly due to the strong interference received from the dominated lineof- sight channels of the UAVs. By forming multiple highly directional beams, millimeter-wave (mmWave) communication technology allows concurrent user transmissions via beam-division multiple access (BDMA), and thus has emerged as a promising solution to mitigate interference for the fifth generation (5G) UAV communication. However, due to the limited number of beams generated in practical mmWave communication systems, conventional BDMA cannot meet the ever increasing capacity requirement. A new multiple access technique is intensely desired. In this article, we integrate mmWave communication with UAV-aided 5G ultra-dense networks, and design a novel link-adaptive constellation- division multiple access (CoDMA) technique. We discuss key challenges in efficient multiple access technique design, and then investigate design principles on new multiplexing methods and beamwidth optimization for interference management in UAV-aided dynamic networks. We further apply flexible constellation division in rateless codes, and put forward the system-level design of CoMDA with beamwidth adaptation to unleash the multiplexing gain. Finally, we show that our design can successfully enable multiple-user access within a single beam without causing any intra-beam interference while efficiently mitigating interference from adjacent beams. We also demonstrate that the proposed design is adaptive to the UAV network dynamics, and can greatly improve the system throughput.

Robust Beamforming for Physical Layer Security in BDMA Massive MIMO

In this paper, we design robust beamforming to guarantee the physical layer security for a multiuser beam division multiple access (BDMA) massive multiple-input multiple-output (MIMO) system, when the channel estimation errors are taken into consideration. With the aid of artificial noise, the proposed design are formulated as minimizing the transmit power of the base station, while providing legal users and the eavesdropper with different signal-to-interference-plus-noise ratio. It is strictly proved that, under BDMA massive MIMO scheme, the initial non-convex optimization can be equivalently converted to a convex semi-definite programming problem and the optimal rank-one beamforming solutions can be guaranteed. In stead of directly resorting to the convex tool, we make one step further by deriving the optimal beamforming direction and the optimal beamforming power allocation in closed-form, which greatly reduces the computational complexity and makes the proposed design practical for real world applications. Simulation results are then provided to verify the efficiency of the proposed algorithm.

Robust Downlink Beamforming for BDMA Massive MIMO System

In this paper, we design robust downlink beamforming against the imperfect channel state information (CSI) for beam division multiple access (BDMA) massive multiple-input multiple output (MIMO) systems. Following a worst-case deterministic model, the proposed design is formulated as minimizing the power consumption of base station (BS) under different signal-to-interference-plus-noise ratio (SINR) constraints. The S-Procedure and semi-definite relaxation (SDR) are used to convert the initial non-convex optimization to a convex semi-definite programming problem. Then the optimality of SDR is strictly proved by showing the rank-one property of the optimal beamforming thanks to the orthogonal channels under BDMA scheme. More importantly, we make one step further by deriving the optimal beamforming directions and optimal beamforming power allocation of the SDR in closed-form, which greatly reduces the optimization complexity and makes the proposed design practical for a real word massive MIMO system. Simulation results are then provided to verify the efficiency of the proposed robust beamforming algorithm.

Improved Design of an Adaptive Massive MIMO Spherical Antenna Array

Massive capacity and connectivity are the main boundaries towards standing the Internet of Everything (IoE) basis and defining modern wireless generation requirements. These needs cannot be achieved by already deployed phased array antenna in terms of distributed and oriented geometry, dimensions and design. We propose in the present paper an innovating massive multiple input multiple output (MIMO) spherical array network aiming to draw a new three-dimensional configuration to enhance the beam steering, improve bandwidth, total capacity and the scan flexibility. Resolved issues in concordance with 5G requirements are adaptive massive MIMO by using millimeter-wave antenna arrays, small cell design and definition of recommended operational frequency considering the International Telecommunication Union (ITU) norms and directives. The new geometric forms of spherical smart antenna could easily scan all 3D space, ensure higher capacity and reach tens of Giga bit per second (Gbps) value besides eradicating energy wastage aspect of Beam Division Multiple Access (BDMA) in base stations. Mathematical design is detailed and performed simulation results are presented using MATLAB software Tool.

On the Performance of Beam Division Nonorthogonal Multiple Access for FDD-Based Large-Scale Multi-User MIMO Systems

For the frequency division duplexing-based large-scale multiple-input multiple-output (MIMO) systems, we consider a multi-user MIMO (MU-MIMO) non-orthogonal multiple access (NOMA) scheme, referred to as beam division-NOMA (BD-NOMA) , which is featured by a long-term feedback-based user grouping and clustering, along with a short-term feedback-based BD-NOMA scheduling. The performance of BD-NOMA is not warranted in practice because near users are severely interfered by strong signals for the far users of other beams, and furthermore, the long-term feedback-based user grouping and clustering might result in short-term inter-beam interference. We consider the short-term feedback-based joint optimization problem of user selection and power allocation for NOMA in each beam and system-wide power allocation for MU-MIMO, dealing with both intra-beam and inter-beam interference at the same time. We formulate a joint optimization problem for a large-scale MIMO system with the multiple channel quality indicators-based short-term feedback. In our analysis, we reformulate the original problem into an equivalent one that can be solved iteratively with the weighted minimum mean square error-based algorithm. Then, the performance analysis is presented to conclude that the proposed optimization is essential for enabling BD-NOMA to outperform beam division multiple access, especially when inter-beam interference becomes critical.

BDMA in Multicell Massive MIMO Communications: Power Allocation Algorithms

We investigate power allocation strategies for beam division multiple access transmission in multicell massive multiple-input-multiple-output (MIMO) communications. Focusing on massive MIMO downlink with only statistical channel state information at serving base stations and multiantenna terminals, the eigenmatrices of channel transmit covariance matrices become identical and independent of terminals. Utilizing these eigenmatrices as precoding matrices, we consider power allocation of beam domain transmission. By treating cochannel user interferences as noises, the objective function of achievable ergodic sum-rate of the multicell massive MIMO downlink reduces to a difference of concave functions. We identify the orthogonality conditions for optimal power allocation. The results show that the transmit power allocated to the users should be nonoverlapping across beams defined by the channel transmit covariance matrices. We present two algorithms to optimize power allocation in the beam space. We also prove the convergence of the algorithms and show that the solution obtained by the algorithms satisfies the orthogonality conditions. Numerical results confirm the efficiency and the improved performance of the proposed algorithms.

5G: MIMO BDMA System Trends and Technology

Beam Division Multipleaccess(BDMA) is The last techniquecame to create the fifth-generation (5G) and solving the problem in the fourth generation (4G). In which base station (BS) allocates private beam to the mobile station (MS) in the system, to increase the capacity and bandwidth of system. For that antenna beam is divides according to the speed and location of mobile stations. In mobile wireless communication the important thing is how to increased limited frequency of the system, improve data rate and good quality of services for user etc. This paper presents information about BDMA and explain the differenttechnologies,and which we want to making future mobile with more powerful and more in demand.Useful thing in BDMA technique is the large number of users to connect at the same time by direction of orthogonal beam from BS by giving multiple access to MS, and increasing the ability of system to be established very big channel. Direction of antenna beam goes off the desired location of MS, and void are placed in undesired direction depend on work environment.

BDMA for Millimeter-Wave/Terahertz Massive MIMO Transmission With Per-Beam Synchronization

We propose beam division multiple access (BDMA) with per-beam synchronization (PBS) in time and frequency for wideband massive multiple-input multiple-output (MIMO) transmission over millimeter-wave (mmW)/Terahertz (THz) bands. We first introduce a physically motivated beam domain channel model for massive MIMO and demonstrate that the envelopes of the beam domain channel elements tend to be independent of time and frequency when both the numbers of antennas at base station and user terminals (UTs) tend to infinity. Motivated by the derived beam domain channel properties, we then propose PBS for mmW/THz massive MIMO. We show that both the effective delay and Doppler frequency spreads of wideband massive MIMO channels with PBS are reduced by a factor of the number of UT antennas compared with the conventional synchronization approaches. Subsequently, we apply PBS to BDMA, investigate beam scheduling to maximize the achievable ergodic rates for both uplink and downlink BDMA, and develop a greedy beam scheduling algorithm. Simulation results verify the effectiveness of BDMA with PBS for mmW/THz wideband massive MIMO systems in typical mobility scenarios.

Beam Division Multiple Access Transmission for Massive MIMO Communications

We study multicarrier multiuser multiple-input multiple-output (MU-MIMO) systems, in which the base station employs an asymptotically large number of antennas. We analyze a fully correlated channel matrix and provide a beam domain channel model, where the channel gains are independent of sub-carriers. For this model, we first derive a closed-form upper bound on the achievable ergodic sum-rate, based on which, we develop asymptotically necessary and sufficient conditions for optimal downlink transmission that require only statistical channel state information at the transmitter. Furthermore, we propose a beam division multiple access (BDMA) transmission scheme that simultaneously serves multiple users via different beams. By selecting users within non-overlapping beams, the MU-MIMO channels can be equivalently decomposed into multiple single-user MIMO channels; this scheme significantly reduces the overhead of channel estimation, as well as, the processing complexity at transceivers. For BDMA transmission, we work out an optimal pilot design criterion to minimize the mean square error (MSE) and provide optimal pilot sequences by utilizing the Zadoff-Chu sequences. Simulations demonstrate the near-optimal performance of BDMA transmission and the advantages of the proposed pilot sequences.