Spatial Channel Models (SCM) used in wireless system simulations are determined by Large-Scale Parameters (LSP). LSPs include delay spread, shadow fading, angle of arrival and departure spread, and Rice K for line-of-sight channels. LSPs are modeled as a spatially correlated random field over the geometry of the network scenario being simulated. The general method is to generate an LSP map on a discrete lattice (or grid) and induce spatial correlation via spatial filtering as determined by the LSP's correlation distance. This step represents a large part of the simulator's computation load, which leads to the use of a coarsely spaced lattice and interpolation from nearest lattice points to arbitrary UE locations on the x-y plane. We investigate the computation vs. fidelity trade associated with LSP generation. We will show that when a coarse grid is employed, there can be significant nonstationary distortion of the LSP correlation due to the interpolation step. We investigate three different interpolators having varying correlation fidelity and computation load.

We examine the design of space-time codes that allow simple encoding and decoding of high and low-priority streams of data. This paper comprises two parts. In the first part we introduce the system model, establish performance and complexity criteria, and introduce "direct-sum" codes that combine existing space-time codes with hierarchical modulation. In this second part, we show that the direct-sum codes of the first part can be greatly improved upon by non-direct-sum designs. We demonstrate unitary-transform\/ codes for two and four antennas. In particular, one such code performs 4 dB better than the direct-sum Alamouti code, with per-bit decoding complexity on one stream that is a bounded function of the rate of the other stream.

Multi-stream codes are used in wireless broadcast services where two or more priority classes of data are transmitted simultaneously, and a receiving terminal may decode one or more of the streams as a function of its receive signal to noise ratio. Present-day commercial cellular-based broadcast services generally utilize hierarchical modulation, a clever technique for embedding high and low-priority streams in a single modulated quadrature symbol. With many cellular standards moving to multiple-transmit antenna configurations, there are opportunities for designing new multi-stream encoding techniques that exploit these antennas. We examine the design of space-time codes that allow simple encoding and decoding of high and low-priority streams of data. A desirable multi-stream space-time code has a combination of good performance and low complexity. Performance is generally measured as coded bit-error rate, assuming max-log maximum aposteriori decoding. Complexity is measured as the effort needed to compute the aposteriori probabilities for either stream. Hierarchical modulation, for single-antenna transmissions, allows each stream to be decoded simply and independently. The paper comprises two parts. In this first part, we establish a general performance criterion for two-stream space-time codes and derive a formula for the complexity of max-log maximum aposteriori decoding of either stream. We also show how existing space-time codes may be combined with hierarchical modulation in a "direct sum". The direct-sum codes have low complexity, but we show in the second part of this paper that these codes can be significantly outperformed by non-direct-sum codes. One of our proposed two-stream codes performs 4 dB better than the Alamouti direct-sum code; it also has the benefit of decoding complexity in one stream that is a bounded function of the rate of the other.

Multiple antenna systems can be used to increase system reliability or to increase system capacity. Initially, space-time codes were designed to achieve one of these two types of gain. Recently, though, a tradeoff between these two system resources has been characterized by the diversity-multiplexing tradeoff. Achieving this optimal performance frontier requires proper coding. For diversity optimality, the signal transmitted from each antenna must redundantly describe the message bits. This redundancy has been quantified by the rate of a space-time code, which relates space-time codebook size to constituent single-input-single-output (SISO) constellation size. Achievable diversity has also been shown to decrease with increasing rates, which establishes the diversity-rate tradeoff. In this work, we consider a generalized notion of the rate of the space-time code, which we refer to as the code rate Rc, and the associated diversity-code rate tradeoff. We then generalize the diversity-multiplexing and diversity-code rate tradeoffs and find that a new diversity-multiplexing tradeoff exists as a function of the code rate.

Recently, there has been a great deal of interest on the performance of MIMO wireless systems as the MIMO fading channel offers an increase in capacity and reliability over that of a SISO channel. When channel state information is not known at the transmitter, the level of performance obtained depends on the degree of cooperation between the transmit antennas. With no cooperation between the antennas, horizontally coded spatial multiplexing is diversity suboptimal since each message bit is encoded and transmitted by only one antenna. An optimal scheme, on the other hand, codes message bits across all transmit antennas. This work generalizes and quantifies the level of cooperation between transmit antennas with the cooperation parameter Rcand then finds upper and lower bounds for the achievable data rates for such a system using a scaled identity transmit covariance matrix. These bounds are found to be tight for certain values of Rcand the data rate Rt. Finally, these bounds are useful in computing the outage probability and diversity order of partially cooperative MIMO systems when channel state information is not known at the transmitter

MIMO wireless systems have been a focus of research for several years, mainly because of the promise of increased channel capacity, extended range, and increased reliability. An aspect of this ongoing research has been concerned with transmit precoding given partial information of the channel. This work focuses on designing a transmit covariance to minimize the probability of outage for a given target data rate over a fading MIMO channel whose distribution is known to the transmitter. This problem is addressed by formulating a convex problem via a heuristic relaxation. Structure of the problem is utilized to simplify the numerical implementation. Finally, the performance of this technique relative to other simpler techniques is considered, therefore showing the utility of this computational technique in evaluating other heuristics.