The multi-input multi-output (MIMO) antenna arrangement technique has been used in different domains of wireless communication for its proven advantages. It has been a source of spatial multiplexing data communication, with evident improvement in data transmission capacity. This paper features one of its applications in a spatial time division multiple access (STDMA) scenario in a wireless mesh network (WMN) environment. As its main aim, the paper provides a new joint routing, dynamic time slot assignment algorithm, and scheduling schemes, based on the utilization of multiuser diversity in the WMN for MIMO link rate.

The paper provides a good literature review of MIMO link rate models, previous joint routing and time assignment methods, and scheduling ideas, along with a good introductory explanation of the different objectives. The link pattern method at slot assignment is criticized. Because of its static non-scheduling policy and disability with multiuser diversity, a node pattern scheme is devised. Next, the authors present system modeling by traditional math.

Using the signal-to-interference-plus-noise ratio (SINR) distribution of data streams, the authors formalize a model to express the longterm average MIMO link transmission rate. A linear programming formula is composed based on the configuration of the mesh network components, arrangement of nodes, antennas, data streams among the transmitters, receiver antennas, and constraints. Because of the growth of the complexity of the formula as the number of nodes and antennas increases, a mediator solution based on the column generator method is proposed. It tries to solve the optimization problem through a two-phase mechanism: the master problem, where linear programming would solve the problem based on a subset of variables, and the subproblem, where it would gradually embrace more variables to refine the master’s solution set. The solution is implemented by an incomplete and greedy algorithm. Implementation issues are discussed next, including opportunistic scheduling. The paper finishes with sections 5, “Performance Evaluation and Comparisons,” and 6, “Conclusion.”

Although the paper has a good mathematical modeling formulation theme, its implementation of algorithmic aspects is not as strong as it should be. More attention to the intrinsic properties of radio communication, like interference, is required. Moreover, it would be better if one topic was covered thoroughly rather than including many incomplete subjects.