The present invention discloses a data transmission method and apparatus. A first access point determines a current working uplink receiving beam, and broadcasts an identifier of the current working uplink receiving beam of the first access point, so that when a first station associated with the first access point determines, according to the identifier of the current working uplink receiving beam of the first access point, that a first transmitting beam at which the first station is currently working is the current working uplink receiving beam of the first access point, the first station performs data transmission with the first access point by using the first transmitting beam. The current working uplink receiving beam of the first access point and a current working uplink receiving beam of a second access point do not overlap in space.

Data transmission method and apparatus

Performance of multi-user transmitter preprocessing assisted MIMO system over correlated frequency-selective channels

An introduction of intelligent interconnectivity for people and things has posed higher demands and more challenges for sixth-generation (6G) networks, such as high spectral efficiency and energy efficiency, ultra-low latency, and ultra-high reliability. Cell-free (CF) massive multiple-input multiple-output (mMIMO) and reconfigurable intelligent surface (RIS), also called intelligent reflecting surface (IRS), are two promising technologies for coping with these unprecedented demands. Given their distinct capabilities, integrating the two technologies to further enhance wireless network performances has received great research and development attention. In this paper, we provide a comprehensive survey of research on RIS-aided CF mMIMO wireless communication systems. We first introduce system models focusing on system architecture and application scenarios, channel models, and communication protocols. Subsequently, we summarize the relevant studies on system operation and resource allocation, providing in-depth analyses and discussions. Following this, we present practical challenges faced by RIS-aided CF mMIMO systems, particularly those introduced by RIS, such as hardware impairments and electromagnetic interference. We summarize corresponding analyses and solutions to further facilitate the implementation of RIS-aided CF mMIMO systems. Furthermore, we explore an interplay between RIS-aided CF mMIMO and other emerging 6G technologies, such as next-generation multiple-access (NGMA), simultaneous wireless information and power transfer (SWIPT), and millimeter wave (mmWave). Finally, we outline several research directions for future RIS-aided CF mMIMO systems.

pdf/ris-aided-cell-free-massive-mimo-systems-for-6g-fundamentals-293qr2jef9.pdf

RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications

Massive MIMO has shown to be a promising candidate for the next generation of mobile communications 5G. Cell free massive MIMO is an implementation in which antennas are distributed throughout the coverage area and the whole area is considered as a single cell. Despite increasing spectral efficiency, cell free massive MIMO has some practical challenges. One challenge is the limited capacity of fronthaul links connecting antennas to the central unit. In this paper, the problem of power weight allocation for a cell free massive MIMO with limited capacity fronthaul links is formulated and solved. The precoded signals for all of the distributed antennas are calculated at the central unit. These signals are then compressed and sent through the limited capacity links to the antennas. Several scenarios are explored, including joint power weight allocation and compression, separate power weight allocation and compression, and no compression. Results show that for limited capacity fronthaul, including compression effect rather than ignoring it, can enhance the performance of power weight allocation considerably.

Cell Free Massive MIMO with Limited Capacity Fronthaul

New generations of wireless communications need to provide users with more bitrates to meet the requirements of new applications. Massive MIMO has shown to be a promising candidate for the next generation of wireless systems 5G. Cell Free Massive MIMO distributes the antennas all around the coverage area and uses all the antennas to cover each user. Despite the increase in user rates, it also creates new challenges. One of the challenges is antenna assignment, which is studied in this paper. A sum-rate maximization problem in the downlink is solved first and then an algorithm is proposed to assign a group of antennas to each user.

Antenna assignment in Cell Free Massive MIMO systems

Multi-cell joint transmission method

This paper focuses on transmit precoding for multiuser MIMO downlink systems. In multiuser MIMO systems, multiuser interference (MUI) and noise are two well-known factors with respect to the system's performance. Block diagonalization (BD) method is proposed to completely eliminate MUI by placing the intended users in the nullspace of all the unintended users. But the BD method imposes a condition on the relation between the number of transmit and receive antennas. In addition, BD method causes the noise enhancement due to not considering noise's influence. Thus, at low and medium signal-to-noise ratio (SNR) regime, the performance of the BD scheme is poor. In this paper, we propose a novel precoding approach for users with multiple antennas to overcome the above mentioned drawbacks of the BD method for multiuser MIMO precoding systems. Simulation results confirm that the proposed algorithm achieves performance improvement over the conventional BD scheme with low complexity. The effect of channel estimate errors on system performance is also studied.

A Transmit Precoding Scheme for Downlink Multiuser MIMO Systems

The invention provides a precoding method and a matrix generating device of a CoMP (coordinated multi-point) multiple-user MIMO (multiple-input multi output) system The method comprises the following steps that: S1, a central control station acquires base station transmitting power Pn (n=1,,K), channel information Hn,i between a base station n and a user i and the signal-to-noise ratio SNRn,i (i=1,K) from each cell base station n (n=1,T) and further obtains the channel information Hi and noise power of each user, wherein T is the number of coordinated cells and K is the number of users in the system; S2, the central control station acquires a complementary channel of each user according to the channel information Hi of each user and carries out channel expansion on each complementary channel to obtain a matrix shown in the specification, wherein I is a unit matrix shown in the specification and Mk represents the number of receiving antennae of a user k; S3, the central control station carries out LQ (leadership quotient) decomposition on the matrix to obtain a unitary matrix Q1; S4, the central control station carries out conjugate transpose on the submatrix of the Qi and multiplies the submatrix subjected to conjugate transpose by Hi, thus obtaining an equivalent channel of each user; S5, the central control station carries out SVD (singular value decomposition) on each equivalent channel so as to obtain a precoding matrix Wi (i=1,,K) of each user; and S6, the central control station obtains the precoding matrix (n=1,T) of each base station according to the precoding matrix Wi (i=1,,K) of each user and transmits each precoding matrix (n=1,T) to the corresponding cell base station to further carry out precoding

Precoding method and matrix generating device of CoMP (coordinated multi-point) multiple-user MIMO (multiple-input multi output) system

In this letter, we propose a novel time switching (TS) transmission scheme for intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN). In the energy harvesting (EH) phase, the operation of IRS is switched between energy harvesting and reflecting to improve the energy transfer. In the information transmitting (IT) phase, the operation of IRS is switched between assisted and unassisted IT to avoid the deficient duration of IT phase when the IRS is energy starved. We formulate an achievable sum-rate maximization problem by jointly optimizing the resource allocation, IRS phase shift and location of the UAV. To address the non-convexity resulting from coupling of variables, we divide original problem into three sub-problems and solve them with the block coordinate descent (BCD) method. The numerical results testify that the proposed scheme can obtain the significant sum-rate gain compared to the traditional TS scheme.

Sum Rate Maximization for Self-Sustainable IRS-Assisted UAV Communications

In this paper, we evaluate the existing transmission schemes in multi-cell environment, such as single-cell transmission with Inter-cell interference (ICI) as well as Collaborative Multi-Point transmission/reception (CoMP) technique in LTE-A, and propose an more effective solution to deal with the inter-cell interference. The proposed transmission structure takes advantage of the cooperation between base stations (BS), and combines both closed-loop and open-loop techniques. With the concept of Effective Channel, the classic Space Frequency Block Coding (SFBC) decode scheme can be used directly in our receiver for single layer transmission. Thus, we prove that the scenario of multiple base stations can employ SFBC conveniently while the performance is guaranteed. Analysis and simulation results show that our method outperforms conventional single cell transmission. Moreover, the proposed transmission scheme can obtain elegant performance enhancement compared with local precoding and global precoding of CoMP in terms of capacity, and doubly reduce the feedback overhead at the same time.

Multi-Cell Collaborative Transmission Combining Closed-Loop and Open-Loop Techniques

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