This paper presents novel ultrareliable and low-latency communication (URLLC) techniques for URLLC services, such as Tactile Internet services. Among typical use cases of URLLC services are teleoperation, immersive virtual reality, cooperative automated driving, and so on. In such URLLC services, new kinds of traffic such as haptic information including kinesthetic information and tactile information need to be delivered in addition to high-quality video and audio traffic in traditional multimedia services. Furthermore, such a variety of traffic has various characteristics in terms of packet sizes and data rates with a variety of requirements of latency and reliability. Furthermore, some traffic may occur in a sporadic manner but requires reliable delivery of packets of medium to large sizes within a low latency, which is not supported by current state-of-the-art wireless communication systems and is very challenging for future wireless communication systems. Thus, to meet such a variety of tight traffic requirements in a wireless communication system, novel technologies from the physical layer to the network layer need to be devised. In this paper, some novel physical layer technologies such as waveform multiplexing, multiple-access scheme, channel code design, synchronization, and full-duplex transmission for spectrally efficient URLLC are introduced. In addition, a novel performance evaluation approach, which combines a ray-tracing tool and system-level simulation, is suggested for evaluating the performance of the proposed schemes. Simulation results show the feasibility of the proposed schemes providing realistic URLLC services in realistic geographical environments, which encourages further efforts to substantiate the proposed work.

Despite significant research efforts in beamforming, the maximum achievable downlink throughput with beamforming in a multi-cell environment is not available due to difficulty in finding optimal downlink beamforming. Thus, to reformulate the problem into a more solvable form, we derive dual uplink throughput optimization problem to multi-cell downlink beam- forming throughput maximization with per-base station (BS) power constraints based on Lagrangian duality. The optimal downlink beamforming is shown to be a minimum mean squared error (MMSE) beamforming in the dual uplink. It is also shown that the dual uplink problem achieves the same optimal throughput as the primal downlink problem.

The feasibility condition of interference alignment (IA) for full-duplex (FD) multiple-input multiple-output (MIMO) cellular networks is considered. A necessary condition and a sufficient condition on the IA feasibility are established, characterizing the optimal sum degrees of freedom (DoF) for a broad class of network topologies. The necessary and sufficient condition is shown specially for a class of symmetric network topologies. The results demonstrate that FD operation at the base station with appropriate IA is able to improve the sum DoF than the conventional half-duplex operation.

We consider in-band full-duplex (FD) vehicular access networks in which a FD vehicular access point (AP) with high mobility simultaneously supports half-duplex (HD) downlink and uplink users with low mobility. We assume no self-interference due to FD operation at the AP and no channel state information known at the transmit side (no channel state information at the transmitter side). We completely characterize the sum degrees of freedom (DoF) by proposing an optimal blind interference alignment scheme, which exploits the difference of channel's temporal correlations between the AP and users, and establishing the matching upper bound on the sum DoF. Performance evaluation shows that the proposed scheme improves the sum rate at the finite signal-to-noise ratio regime compared to the conventional HD system.

We propose a max-min fairness (MMF) design method in a multi-antenna downlink network, where rate-splitting multiple access (RSMA) is adopted. A main aim in the considered MMF problem is providing uniformly good rates to users, by carefully controlling the rate of each private and common message, respectively. Solving this problem is challenging since multiple optimization variables, i.e., beamforming vectors and common message portions, are intricately intertwined in a non-tractable objective function. To resolve these obstacles, we first split a whole problem into two stages. In the first stage, we identify beamforming vectors given common message portion by exploiting the LogSumExp (LSE) approximation technique and the novel generalized power iteration (GPI) framework. In the second stage, we determine common message portions under fixed beamforming vectors. Iterating these two stages, we jointly design beamforming vectors and common message portion accordingly. Via simulations, we demonstrate that our method outperforms existing other frameworks in terms of the minimum rate, while requiring extremely small computational complexity.

Full-duplex (FD) cellular networks are considered in which an FD base station (BS) simultaneously supports a set of half-duplex (HD) downlink (DL) users and a set of HD uplink (UL) users. The transmitter and the receiver of the BS are equipped with reconfigurable antennas, each of which can choose its transmit or receive mode from several preset modes. Under the no self-interference assumption arisen from an FD operation at the BS, the sum degrees of freedom (DoF) of FD cellular networks is investigated for both no channel state information at the transmit side (CSIT) and the partial CSIT. In particular, the sum DoF is completely characterized for the no CSIT model and an achievable sum DoF is established for the partial CSIT model, which improves the sum DoF of the conventional HD cellular networks. For both no CSIT and partial CSIT models, the results show that the FD BS with reconfigurable antennas can double the sum DoF even in the presence of user-to-user interference as both the numbers of DL and UL users and preset modes increase. It is further demonstrated that such DoF improvement indeed yields the sum rate improvement at the finite and operational signal-to-noise ratio regime.