In this paper, we study millimeter-wave (mmWave) and sub-Terahertz (THz) communications with array- of-subarray architecture. To obtain the dominant channel information, two multi-resolution codebooks are designed for beamforming training by exploiting subarray coordination, where beam enhancement and broadening are jointly implemented. Then, based on the proposed codebooks, a hierarchical beamforming training strategy is developed to enable simultaneous training for multiple users. Simulation results are provided to show that the proposed multi- resolution codebooks could significantly increase the beam gain. Also, the effectiveness of the hierarchical beamforming training is verified.

Millimeter-wave (mmWave) and sub-Terahertz (THz) communications are compelling as an enabler for next-generation wireless networks. In this paper, we study mmWave and sub-THz systems with array-of-subarray architecture. To accommodate the ultrabroad bandwidth in the mmWave and sub-THz bands, time-delay phase shifters are introduced in system design. Our goal is to investigate beamforming training with hybrid processing to extract the dominant channel information, which would fully exploit channel characteristics while respecting the nature of circuit hardware. In particular, codebooks based on time-delay phase shifters are defined and structured. Then, two multi-resolution time-delay codebooks are designed through subarray coordination. One is built on adaptation of physical beam directions, and the other relies on dynamic approximation of beam patterns. Also, a low-complexity system implementation with modifications on the time-delay codebooks is studied. Furthermore, based on the proposed codebooks, a hierarchical beamforming training strategy with reduced overhead is developed to enable simultaneous training for multiple users. Simulation results show that the proposed multi-resolution time-delay codebooks could provide sufficient beam gains and are robust over large bandwidth. Also, the effectiveness of the hierarchical beamforming training is verified.

Emerging millimeter-wave (mmWave) and Terahertz (THz) systems is a promising revolution for next-generation wireless communications. In this paper, we study an indoor multi-user mmWave and sub-THz system with large antenna arrays, where two different types of architecture, the fully-connected structure and the array-of-subarray structure, are investigated. Specifically, the Doherty power amplifier (PA) is adopted to improve the PA efficiency of the system, and the associated nonlinear system power consumption models with insertion power loss are developed. By capturing the characteristics of the mmWave and sub-THz channels, we design different hybrid beamforming schemes for the two structures with low complexity. We further compare the achievable rates of the two structures and show that, with the insertion loss, the achievable rate of the array-of-subarray structure is generally larger than that of the fully-connected structure. Moreover, we propose the optimal power control strategies for both structures to maximize the energy efficiency of the system and demonstrate that the energy efficiency of the array-of-subarray structure outperforms that of the fully-connected structure. Simulation results are provided to compare and validate the performance of the two structures, where the array-of-subarray structure shows a great advantage over the fully-connected structure in both spectral efficiency and energy efficiency.

In this paper, we study a multi-user indoor Terahertz (THz) communication system with multiple antenna subarrays. By exploiting the characteristics of the THz channel and the capabilities of large antennas, we design a hybrid beamforming scheme to compensate the severe path loss while keep the system in low complexity. In particular, with the analog beamsteering searching in radio frequency (RF) domain, antenna subarrays are partitioned on a user basis, where data streams are transmitted and steered via a group of subarrays to a specific user. Then, the zero- forcing digital beamformer is implemented at baseband for interference cancellation among different users. Simulation results are provided to verify the effectiveness of the proposed hybrid beamforming scheme for the multi-user THz system, which shows great advantages over the schemes with random subarray assignment and analog-only beamsteering.

Terahertz (THz) communication is envisioned as a key technology for next-generation ultra-high-speed wireless systems. In this paper, we study an indoor multi-user THz communication system with multiple antenna subarrays. To capture the distance-frequency-dependent characteristics of THz channels, we design a hybrid beamforming scheme with distance-aware multi-carrier transmission, including analog beamforming for user grouping and interference cancellation in radio-frequency (RF) domain and digital beamforming with dynamically selected subarrays at baseband. Specifically, an adaptive power allocation and low-complexity antenna subarray selection policy is developed to serve different users at different distances and reduce the cost of active RF circuits simultaneously, where two greedy subarray selection algorithms are proposed. The effectiveness of the proposed adaptive hybrid beamforming and antenna subarray selection algorithms is verified through simulation results, which achieves significant gains over other nonadaptive and non-distance-aware schemes.

Terahertz (THz) communications promise to be the next frontier for wireless networks. Novel solutions should be explored to overcome the hardware constraints and the severe path loss. In this paper, we study a low-complexity indoor THz communication system with antenna subarrays. The Saleh-Valenzuela (S-V) channel model is modified to characterize the THz channel. By exploiting the hybrid beamforming with multiple subarrays, we analyze the ergodic capacity of the system and obtain an upper bound. Furthermore, with the analysis of performance degradation for the uncertainty in THz phase shifters, we provide a guidance on the design of antenna subarray size and number for certain long-term data rate requirements with different distances. Simulation results validate the effectiveness of the ergodic capacity upper bound, and show that the proposed THz system and antenna array structure can efficiently achieve capacity gains and support THz communications.

In this paper, we study antenna arrays for an indoor Terahertz (THz) communication system. The Saleh-Valenzuela (S-V) channel model is modified to characterize the THz channel. We analyze the relationship between the ergodic capacity with hybrid beamforming and the antenna subarray number, and obtain an upper bound. Specifically, the required number of sub-arrays is derived under certain long-term data rate requirement. Simulation results are provided to evaluate the performance of the THz system and verify the analytical results.

In this paper, we study a multiuser indoor Terahertz (THz) communication system with antenna array. To capture the distance-frequency dependent peculiarities of THz channels, we design a distance-aware multi-carrier transmission scheme with hybrid beamforming and antenna subarray selection. Specifically, a low complexity greedy subarray selection algorithm is proposed. Simulation results are provided to verify the effectiveness of the transmission policy as well as the antenna subarray selection algorithm for the multiuser THz system.

In this paper, we study the cross layer design and optimization for delay quality-of-service (QoS) provisioning in spectrum sharing femtocell networks. Our goal is to find the optimal resource allocation policy to maximize the throughput for each femtocell user, addressing the co-channel interference problem in the physical layer and the individual statistical delay-QoS guarantee problem from the upper layers. The statistical delay-QoS requirement is characterized by the QoS exponent. By integrating the concept of effective capacity, the cross-layer optimization problem is formulated as an effective capacity maximization game. With partial dual decomposition, this game is solved through a hierarchical structure. Specifically, we derive the optimal power allocation policy for femtocell users and design a distributed algorithm to obtain the Nash Equilibrium (N.E.). Numerical results show that the proposed policy can efficiently improve the performance of the networks.

Two-way relaying promises considerable improvements on spectral efficiency in wireless relay networks. While most existing works focus on physical layer approaches to exploit its capacity gain, the benefits of two-way relaying on upper layers are much less investigated. In this paper, we study the cross-layer design and optimization for delay quality-of-service (QoS) provisioning in two-way relay systems. Our goal is to find the optimal transmission policy to maximize the weighted sum throughput of the two users in the physical layer while guaranteeing the individual statistical delay-QoS requirement for each user in the datalink layer. This statistical delay-QoS requirement is characterized by the QoS exponent. By integrating the concept of effective capacity, the cross-layer optimization problem is equivalent to a weighted sum effective capacity maximization problem. We derive the jointly optimal power and rate adaptation policies for both three-phase and two-phase two-way relay protocols. Numerical results show that the proposed adaptive transmission policies can efficiently provide QoS guarantees and improve the performance. In addition, the throughput gain obtained by the considered three-phase and two-phase protocols over direct transmission is significant when the delay-QoS requirements are loose, but the gain diminishes at tight delay requirements. It is also found that, in the two-phase protocol, the relay node should be placed closer to the source with more stringent delay requirement.

In this paper, we consider the cross-layer design for delay quality-of-service (QoS) provisioning in two-way relay systems. We aim to find the optimal resource allocation policy to maximize the weighted sum-rate while guaranteeing the statistical delay-QoS requirements for both users. The delay requirement is characterized as the QoS exponent. With the integration of the concept of effective capacity, the cross-layer optimization problem is equivalent to a weighted sum effective capacity maximization problem. We derive the optimal joint power and rate adaptation policy for the two-phase two-way relaying. Numerical results show that the proposed policy can efficiently support diverse QoS requirements and significantly improve the performance compared with both the fixed power scheme and the weight-based method.

We study the transmission strategy for a system consisting of two pairs of two-way communication links. The information exchange between the two nodes in each pair can only occur with the help of the nodes in the other pair. A novel transmission protocol, named Rotating Decode-and-Forward (RDF) is proposed. In this protocol, the two pairs take turns to forward the signal for each other while having their own information embedded in the signal-to-forward by applying physical layer network coding. The achievable rate region of this protocol is derived. Numerical examples show that proposed RDF protocol can provide significantly higher spectral efficiency than conventional protocols where the transmissions of information signal and signal-to-forward are carried out separately.