Abstract-We investigate the evolution of line of sight (LOS) blockage over both time and space for vehicle-to-vehicle (V2V) channels. Using realistic vehicular mobility and building and foliage locations from maps, we first perform LOS blockage analysis to extract LOS probabilities in real cities and on highways for varying vehicular densities. Next, to model the time evolution of LOS blockage for V2V links, we employ a three-state discrete-time Markov chain comprised of the following states: i) LOS; ii) non-LOS due to static objects (e.g., buildings, trees, etc.); and iii) non-LOS due to mobile objects (vehicles). We obtain state transition probabilities based on the evolution of LOS blockage. Finally, we perform curve fitting and obtain a set of distance-dependent equations for both LOS and transition probabilities. These equations can be used to generate time-evolved V2V channel realizations for representative urban and highway environments. Our results can be used to perform highly efficient and accurate simulations without the need to employ complex geometry-based models for link evolution. I. INTRODUCTIONIn contrast to existing cellular networks that focus primarily on increasing the mobile data rates, fifth-generation (5G) network is expected to efficiently support the so-called vertical industries (e.g., industrial, eHealth, and automotive vertical, among other). Supporting automotive vertical, in the form of vehicle-to-anything (V2X) communication, is seen as one of the most challenging tasks for 5G networks, particularly in terms of end-to-end latency and reliability [1].One of the key distinguishing features of V2X communication is the high mobility, possibly on both sides of the link (as in the case of V2V communication). Another salient aspect of V2X communication is that it is often related to safety, either directly (e.g., emergency braking, intersection collision avoidance application [2], etc.) or indirectly (e.g., platooning, lane-change maneuvers, etc.). To ensure that V2X communication systems can support the application requirements efficiently, a key initial step is realistically defining the channel characteristics for different environments (e.g., urban, highway, rural) and V2X communication types (e.g., V2V, V2I, V2P). Given the V2X application requirements, one of the most relevant aspects of channel modeling is the time evolution of V2V links and the related concept of spatial consistency. Time and space evolution of LOS blockage refers to time-consistent realization of LOS blockage for V2V channels, based on the location of the transmitter (Tx), the receiver (Rx), and the composition of their surroundings. Consistent LOS blockage realization is important in order to assign the appropriate path loss, shadowing, small-scale, and large-scale parameters over time and space. This implies that there should be a continuity in terms of vehicle locations over time (i.e., requiring a continuous vehicle movement) and in terms of scatterer distribution around the vehicles.In the realm of the 3GPP...

This paper considers a downlink unicast transmission in a multi-cell network with multiple users. In a network with frequency reuse-1, inter-cell interference is a limiting factor. The max-min beamforming (MB) technique enables a balancing of the signal-to-interference-plus-noise ratio among all users in a network under a power budget. Thus, a fair distribution of the achievable rate can be achieved. The MB problem (MBP) is non-convex in general. However, if instantaneous channel state information is available, the MBP has an equivalent quasi-convex form and can be optimally solved with an efficient algorithm based on a convex solver.In addition to this convex solver based solution, this paper considers a so-called surrogate dual problem of the MBP with, per-antenna and per-antenna array power constraints. The surrogate dual problem combines multiple power constraints to a single power constraint. Furthermore, the surrogate dual problem can be efficiently solved for long-term channel state information (CSI) in the form of spatial correlation matrices. Strong duality is proved for instantaneous CSI and long-term CSI in the form of higher rank spatial correlation matrices. With the surrogate dual problem, a fast algorithm for the MBP is presented. The convergence issue is discussed. Numerical results verify the convergence and the performance of the proposed algorithm.

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