In this letter, two novel coordinated beamforming techniques are developed to enhance the performance of non-orthogonal multiple access combined with multiple-input multiple-output communication in the presence of inter-cell interference. The proposed schemes successfully deal with inter-cell interference, and increase the cell-edge users' throughput, which in turn improves user fairness. In addition, they increase the number of served users, which makes them suitable for 5G networks where massive connectivity and higher spectral efficiency are required. Numerical results confirm the effectiveness of the proposed algorithms.

Fifth generation wireless standards require much lower latency than what current wireless systems can guarantee. The main challenge in fulfilling these requirements is the development of short packet transmission, in contrast to most of the current standards, which use a long data packet structure. Since the available training resources are limited by the packet size, reliable channel and interference covariance estimation with reduced training overhead are crucial to any system using short data packets. In this paper, we propose an efficient receiver that exploits useful information available in the data transmission period to enhance the reliability of the short packet transmission. In the proposed method, the receive filter (i.e., the sample covariance matrix) is estimated using the received samples from the data transmission without using an interference training period. A channel estimation algorithm to use the most reliable data symbols as virtual pilots is employed to improve quality of the channel estimate. Simulation results verify that the proposed receiver algorithms enhance the reception quality of the short packet transmission.

In the upcoming 6G era, multiple access (MA) will play an essential role in achieving high throughput performances required in a wide range of wireless applications. Since MA and interference management are closely related issues, the conventional MA techniques are limited in that they cannot provide near-optimal performance in universal interference regimes. Recently, rate-splitting multiple access (RSMA) has been gaining much attention. RSMA splits an individual message into two parts: a common part, decodable by every user, and a private part, decodable only by the intended user. Each user first decodes the common message and then decodes its private message by applying successive interference cancellation (SIC). By doing so, RSMA not only embraces the existing MA techniques as special cases but also provides significant performance gains by efficiently mitigating inter-user interference in a broad range of interference regimes. In this article, we first present the theoretical foundation of RSMA. Subsequently, we put forth four key benefits of RSMA: spectral efficiency, robustness, scalability, and flexibility. Upon this, we describe how RSMA can enable ten promising scenarios and applications along with future research directions to pave the way for 6G.

Rate-splitting multiple access (RSMA) is a key enabling technology for beyond 5 G networks due to its robustness against imperfect channel knowledge. In this paper, we consider both the imperfect channel state information (CSI) at the receiver (CSIR) and imperfect CSI at the transmitter (CSIT) and propose a max-min fairness optimization framework relying on RSMA to guarantee each user's minimum level of quality of service (QoS). First, we formulate the max-min fairness optimization problem that has non-convexity. To transform the non-convex problem into a convex problem, we apply the semi-definite relaxation (SDR) and convex-concave procedure (CCP) to the proposed algorithm. From simulation results, we confirm that RSMA is still a robust scheme over conventional multiple access schemes for both imperfect CSIT and CSIR.

As a key technology to meet the ever-increasing data rate demand in beyond 5G and 6G communications, millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems have gained much attention recently. To make the most of mmWave massive MIMO systems, acquisition of accurate channel state information (CSI) at the base station (BS) is crucial. However, this task is by no means easy due to the CSI feedback overhead induced by the large number of antennas. In this paper, we propose a parametric CSI feedback technique for mmWave massive MIMO systems. Key idea of the proposed technique is to compress the mmWave MIMO channel matrix into a few geometric channel parameters (e.g., angles, delays, and path gains). Due to the limited scattering of mmWave signal, the number of channel parameters is much smaller than the number of antennas, thereby reducing the CSI feedback overhead significantly. Moreover, by exploiting the deep learning (DL) technique for the channel parameter extraction and the MIMO channel reconstruction, we can effectively suppress the channel quantization error. From the numerical results, we demonstrate that the proposed technique outperforms the conventional CSI feedback techniques in terms of normalized mean square error (NMSE) and bit error rate (BER).

With the advancement of information and communication technologies (ICTs), the way we live and communicate with each other is changing rapidly. As urban environments continue to evolve, the smart sustainable city (SSC) has sparked considerable attention. We are hoping for a new era in which numerous devices and machines including vehicles, sensors, and robots are all connected to communicate, respond, and operate in real time. The next-generation communication system, the sixth generation (6G), is expected to play a crucial role in improving the efficiency of urban operations and services. In this paper, we first provide the recent trends and key features of standardization in the SSC. To make the future SSC, we highlight key candidate technologies of 6G such as non-terrestrial networks, advanced mobile edge computing, vision-aided wireless communication, artificial intelligence (AI)-based wireless communication, and integrated sensing and communication. We put forth the main technical challenges given to each prime technology along with the potential benefits to pave the way for 6G-enabled SSC. We further address how the potential benefits of prime technologies enable various urban practice cases for 6G-enabled SSC.