New generation communications systems try to increase capacity by, among other things, adding more degrees of freedom such as multiple antennas and enabling them with smart algorithms to mitigate multipath.  In one simple interpretation, multiple antennas can be driven in such a way as to offer a pattern that can distinguish among different Directions of Departure and/or Arrival and, with appropriate phasing at baseband, force signals to combine for maximum throughput.  It is, therefore, obvious that, by design, Multiple Input Multiple Output (MIMO) enabled communication system need to have their antennas designed and evaluated in the context of the propagation environment.  While, for instance, traditional Single Input Single Output (SISO) systems have been treated with link budgets whereby the gain of the antennas may be paramount, in MIMO systems, depending on the level of multipath, a lower gain array may outperform the higher gain one for certain applications.
Additionally, as the cost of a transceiver is higher than that of an antenna, it is reasonable to expect products with more antennas on them than transceivers and equipped with a selection algorithm to adapt according to the environment at hand.  From these simple considerations, it becomes clear that, especially for MIMO systems, the design of products has to take into account the antennas, the propagation environment, the link layer, the Media Access Control (MAC) layer as well as elements of the networking layer.

With the advent of the latest WiFi and 4G technologies, MIMO based telecommunication systems have been already established in various world markets.  They feature several antennas, both on the base station side and the subscriber side of the link to maximize the data throughput.  A MIMO system accomplishes this by an elaborate process of calibrating itself and figuring out where the power is coming from so that it can, among other things, beamform to the source of the energy.  This “channel estimation” and the subsequent actions are a crucial part of the “smart algorithms” that drive MIMO based wireless systems.  In Time Division Duplex (TDD) systems, since both Transmission and Reception take place at the same frequencies, channel estimation is done by sending pilot signals, a priori known to the Base and the Subscriber, and detecting their distortion after travelling through the channel.  Additionally, a dedicated transceiver is utilized to perform “calibration” of the front end rf part between the baseband and the antennas.  In order to minimize the time spent on such system calibration and channel estimation procedures, “reciprocity” over the air channel estimation is often assumed.  That is, the channel between the antenna ports of the Base and the Subscriber is assumed “reciprocal” and pilot signals for channel estimation are only sent from the Subscriber to the Base (Uplink channel sounding).  Obviously, the notion of Base and Subscriber is just a convenience when it comes to the calibration and channel estimation.  The precise nature of the calibration and channel estimation procedure can be modified to take into account the specifics of the system, including mobility.  A very simplified diagram of a typical TDD MIMO system is shown below.



In order for the Base to beamform to the Subscriber, it has to weigh the signal leaving each antenna by a certain amount at the baseband.  The precise weights depend on the transfer function of the Downlink channel.  Through the calibration and the Uplink channel sounding procedure, the Base can perform channel estimation and predict the Downlink channel.  However, to date, many simplifications are made as to the nature of the baseband to baseband transfer function.  These simplifications relate to the antenna coupling as well as the mismatches between the antennas and their transceivers. 

we employ a fundamental and electromagnetically exact formulation of the problem.  In this formulation, we consider all the relevant RF behavior and we arrive at a systematic way of predicting the performance of the link under various electrical and rf properties of the system in various environments.  This gives us the tools and information necessary to design pioneering antennas for any multi antenna systems.  In particular, we are in a position to assess the various performance tradeoffs involving antenna size, cost, coverage, data rate (throughput) in various environments exhibiting multipath.