29927487
Optimization of antenna configuration for MIMO systems
In this letter, we investigate the issue of selecting the number of antennas at the base station and at the mobile to optimize ergodic capacity of a multiple-input/multiple-output system, when the costs of implementing antennas at the base station and at the mobile are unequal. Total system capacity, defined as a linear combination of the uplink and downlink ergodic capacity, is used as the objective function to be maximized. The asymptotic expression for the ergodic capacity is used as an approximation. The limiting case gives some insight on how the ratio of the number of antennas at the base station to the number of antennas at the mobile may change with signal-to-noise ratio and cost ratio when the total system capacity is maximized.
43356203
Robust transforms for channel estimator in clustered OFDM for high rate wireless data
Clustered OFDM can provide in-band diversity gain for wideband wireless channels. It is a promising technique for high-rate wireless packet data access, such as mobile multimedia communications. Due to smaller size of each cluster for clustered OFDM than for classical(non-clustered) OFDM, edge effects can be very large. We present new transforms for channel estimators in clustered OFDM systems. The new transforms are independent of the channel delay profiles and can effectively mitigate the edge effects. Computer simulation shows that the performance of clustered OFDM with the estimator using the new transforms is very close to the performance with the optimum estimator that depends on the channel delay profile. For the typical-urban or hilly-terrain delay profiles, clustered OFDM using the new transform based estimator is almost as good as classical OFDM with transmitter diversity.
5907828
Error correcting least-squares Subspace algorithm for blind identification and equalization
Abstract A subspace based blind channel identification algorithm using only the fact that the received signal can be oversampled is proposed. No direct use is made in this algorithm of either the statistics of the input sequence or even of the fact that the symbols are from a finite set and therefore this algorithm can be used to identify even channels in which arbitrary symbols are sent. Using this algorithm as a base and using the extra information which becomes available when the transmitted symbols are from a known finite set, the EC-LS-Subspace algorithm is derived. The EC-LS-Subspace algorithm operates directly on the data domain and therefore avoids the problems associated with other algorithms which use the statistical information contained in the received signal directly. In the noiseless case, if some conditions are met, it is possible for the proposed Basic Subspace algorithm to identify the channel exactly using an observation interval of just ( J +2) T , if the length of the impulse response of a channel is JT , T being the symbol interval. In the noisy case, simulations have shown that the channel can be identified accurately by using a very small observation interval (comparable to ( J +2) T ).
8467998
Truncation for Low-Complexity MIMO Signal Detection
Joint maximum-likelihood (JML) detector may be used in memoryless multiple-input multiple-output (MIMO) systems to obtain optimal detection performance. However, JML detector performs an exhaustive search and has prohibitively large decoding complexity. To reduce the complexity of MIMO signal detection, minimum mean-square-error (mmse) linear detector (LD), decision-feedback detector (DFD), group detector, and sphere detector (SD) may be used. In this correspondence, we propose a truncation based detector for low-complexity MIMO signal detection, and give theoretical insight into the design and performance of such a detector. We study bitruncation in detail and present two bitruncation approaches. These approaches have low-complexity, and computer simulation results show that they outperform mmse-LD and mmse-DFD
8483401
Optimum spatial-temporal receiver for wireless systems with ISI and CCI
Spatial-temporal processing is an effective technique for wireless systems with antenna arrays to suppress co-channel interference. In this paper, spatial-temporal receive filters for multiple receiver systems with intersymbol interference (ISI), co-channel interference (CCI), and additive white Gaussian noise (AWGN) are investigated. An analogical spatial-temporal matched filter that is optimum for any following T-spaced processor with any reasonable criterion of goodness is found. Therefore, it allows co-channel interference suppression and equalization to be treated separately.
9766004
A PTAS for Minimizing Total Completion Time of Bounded Batch Scheduling
We consider a batch processing system {pi : i = 1, 2,..., n} where pi is the processing time of job i, and up to B jobs can be processed together such that the handling time of a batch is the longest processing time among jobs in the batch. The number of job types m is not fixed and all the jobs are released at the same time. Jobs are executed nonpreemptively. Our objective is to assign jobs to batches and sequence the batches so as to minimize the total completion time. The best previously known result is a 2-approximation algorithm due to D. S. Hochbaum and D. Landy [6]. In this paper, we establish the first polynomial time approximation scheme (PTAS) for the problem.
1876314
A 2-Approximation Algorithm for Path Coloring on Trees of Rings
A tree of rings is an undirected graph obtained from a tree by replacing each node of the tree with a cycle and then contracting the edges of the tree so that two cycles corresponding to the two end-nodes of any edge have precisely one node in common. Given a set of paths on a tree of rings, the routing problem is to color the paths with the smallest number of colors so that any two paths sharing an edge are assigned different colors. We present a 2-approximation algorithm in this paper.
29830975
A PTAS for Minimizing Total Completion Time of Bounded Batch Scheduling
We consider a batch processing system {pi : i = 1, 2,…,n} where pi is the processing time of job i, and up to B jobs can be processed together such that the handling time of a batch is the longest processing time among jobs in the batch. The number of job types m is not fixed and all the jobs are released at the same time. Jobs are executed non-preemptively. Our objective is to assign jobs to batches and sequence the batches so as to minimize the total completion time. The best previously known result is a 2–approximation algorithm. In this paper, we establish the first polynomial time approximation scheme (PTAS) for the problem.
8845811
Contextual Inference in Contour-Based Stereo Correspondence
Standard approaches to stereo correspondence have difficulty when scene structure does not lie in or near the frontal parallel plane, in part because an orientation disparity as well as a positional disparity is introduced. We propose a correspondence algorithm based on differential geometry, that takes explicit advantage of both disparities. The algorithm relates the 2D differential structure (position, tangent, and curvature) of curves in the left and right images to the Frenet approximation of the (3D) space curve. A compatibility function is defined via transport of the Frenet frames, and they are matched by relaxing this compatibility function on overlapping neighborhoods along the curve. The remaining false matches are concurrently eliminated by a model of “near” and “far” neurons derived from neurobiology. Examples on scenes with complex 3D structures are provided.
1247256
Differential Geometric Consistency Extends Stereo to Curved Surfaces
Traditional stereo algorithms implicitly use the frontal parallel plane assumption when exploiting contextual information, since the smoothness prior biases towards constant disparity (depth) over a neighborhood. For curved surfaces these algorithms introduce systematic errors to the matching process. These errors are non-negligible for detailed geometric modeling of natural objects (e.g. a human face). We propose to use contextual information geometrically. In particular, we perform a differential geometric study of smooth surfaces and argue that geometric contextual information should be encoded in Cartan's moving frame model over local quadratic approximations of the smooth surfaces. The result enforces geometric consistency for both depth and surface normal. We develop a simple stereo algorithm to illustrate the importance of using such geometric contextual information and demonstrate its power on images of the human face.