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Millimeter-wave (mmWave) and ultra-dense networks are two key technologies for the fifth-generation (5G) and beyond communication system. However, the ultra-dense deployment of small base stations (SBSs) might introduce severe interference to users that connect to SBSs. This paper analyzes the performance of 5G communication networks where the SBSs with coordinated beamforming, operating at mmWave frequency band and macro base stations (MBSs) operating at sub-6 GHz coexist. First, by utilizing a stochastic geometry approach, we obtain the cell association probability expressions in terms of different cell association biases, base station density ratios and probabilities of line of sight (LoS) link. Furthermore, we propose a clustering method to choose some SBSs to eliminate intra-cell interference. Then, we put forward an average distance from the Kth SBS to a user to obtain signal-to-interference-ratio (SINR) and rate coverage probability expressions. The simulation results validate the correctness of the expressions, and indicate that the optimal cardinality of coordinated SBSs increases with the density of SBSs. In addition, the relationship between the cluster size K and the average energy efficiency is obtained, which can be used to guide the coordination principle in 5G and beyond communication systems. [ABSTRACT FROM AUTHOR]

Moving networks (MNs) with moving base stations (BSs) provide ubiquitous and constant services to cellular devices/user equipment (UEs) in 5-th generation systems. Moving BSs are mounted on top of vehicles. To describe the randomness of the BSs, a tractable stochastic geometry model for MNs is proposed. A definition of the conditional success probability and meta distribution (MD) of the signal-to-interference ratio (SIR) for MNs is proposed. The MD is used to assess the benefits of MNs. In single-tier MNs with high mobility, we determine the moments of the conditional success probability given the point process for the calculation of the MD and the mean local delay. The results show that the mean local delay is finite and the variance is reduced to 0. A closed-form approximation of the variance is proposed for general mobility levels. Using the approximated variance, we propose a beta approximation of the MD. The single-tier model is then extended to a two-tier heterogeneous MN model. Tractable expressions of the mean success probability and the variance for both the overall network and the typical UE in each tier are obtained. They reveal that moving BSs can reduce the variance among UEs while keeping the mean success probability constant. [ABSTRACT FROM AUTHOR]

The objective of maximizing the minimum Euclidean distance between two received data vectors via real-valued linear precoding is considered for multiple-input multiple-output (MIMO) systems with arbitrary dimensions. Assuming that perfect channel state information (CSI) is available at both the transmitter side and the receiver side, a novel low-complexity precoding algorithm is proposed to recursively construct the full-rank, the rank-deficient and the rank-one precoders with respect to particular channel realization. From the lattice theoretical perspective, the full-rank precoder is generated by using well-known dense packing lattices, which can also be recursively involved into the construction of higher-dimensional rank-deficient precoders. Moreover, the optimal solution is clearly figured out for the specific case of rank-one precoder. The closed-form expression of the achievable minimum distance is obtained and the analytical results reveal the performance bounds for different rank-constraint precoders. Simulation results validate the efficiency of the proposed precoder as compared with the state of the art. [ABSTRACT FROM PUBLISHER]