Fairness in Multiuser Systems with Polymatroid Capacity Region

For a wide class of multi-user systems, a subset of capacity region which includes the corner points and the sum-capacity facet has a special structure known as polymatroid. Multiaccess channels with fixed input distributions and multiple-antenna broadcast channels are examples of such systems. Any interior point of the sum-capacity facet can be achieved by time-sharing among corner points or by an alternative method known as rate-splitting. The main purpose of this paper is to find a point on the sum-capacity facet which satisfies a notion of fairness among active users. This problem is addressed in two cases: (i) where the complexity of achieving interior points is not feasible, and (ii) where the complexity of achieving interior points is feasible. For the first case, the corner point for which the minimum rate of the active users is maximized (max-min corner point) is desired for signaling. A simple greedy algorithm is introduced to find the optimum max-min corner point. For the second case, the polymatroid properties are exploited to locate a rate-vector on the sum-capacity facet which is optimally fair in the sense that the minimum rate among all users is maximized (max-min rate). In the case that the rate of some users can not increase further (attain the max-min value), the algorithm recursively maximizes the minimum rate among the rest of the users. It is shown that the problems of deriving the time-sharing coefficients or rate-spitting scheme can be solved by decomposing the problem to some lower-dimensional subproblems. In addition, a fast algorithm to compute the time-sharing coefficients to attain a general point on the sum-capacity facet is proposed.Comment: Submitted To IEEE Transactions on Information Theory, June 200

Multiple-Description Coding by Dithered Delta-Sigma Quantization

We address the connection between the multiple-description (MD) problem and Delta-Sigma quantization. The inherent redundancy due to oversampling in Delta-Sigma quantization, and the simple linear-additive noise model resulting from dithered lattice quantization, allow us to construct a symmetric and time-invariant MD coding scheme. We show that the use of a noise shaping filter makes it possible to trade off central distortion for side distortion. Asymptotically as the dimension of the lattice vector quantizer and order of the noise shaping filter approach infinity, the entropy rate of the dithered Delta-Sigma quantization scheme approaches the symmetric two-channel MD rate-distortion function for a memoryless Gaussian source and MSE fidelity criterion, at any side-to-central distortion ratio and any resolution. In the optimal scheme, the infinite-order noise shaping filter must be minimum phase and have a piece-wise flat power spectrum with a single jump discontinuity. An important advantage of the proposed design is that it is symmetric in rate and distortion by construction, so the coding rates of the descriptions are identical and there is therefore no need for source splitting.Comment: Revised, restructured, significantly shortened and minor typos has been fixed. Accepted for publication in the IEEE Transactions on Information Theor

Communication over MIMO Multi-User Systems: Signalling and Fairness

Employment of the multiple-antenna transmitters/receivers in communication systems is known as a promising solution to provide high-data-rate wireless links. In the multi-user environments, the problems of signaling and fairness for multi-antenna systems have emerged as challenging problems. This dissertation deals with these problems in several multi-antenna multi-user scenarios. In part one, a simple signaling method for the multi-antenna broadcast channels is proposed. This method reduces the MIMO broadcast system to a set of parallel channels. The proposed scheme has several desirable features in terms of: (i) accommodating users with different number of receive antennas, (ii) exploiting multi-user diversity, and (iii) requiring low feedback rate. The simulation results and analytical evaluations indicate that the achieved sum-rate is close to the sum-capacity of the underlying broadcast channel. In part two, for multiple-antenna systems with two transmitters and two receivers, a new non-cooperative scenario of data communication is studied in which each receiver receives data from both transmitters. For such a scenario, a signaling scheme is proposed which decomposes the system into two broadcast or two multi-access sub-channels. Using the decomposition scheme, it is shown that this signaling scenario outperforms the other known non-cooperative schemes in terms of the achievable multiplexing gain. In particular for some special cases, the achieved multiplexing gain is the same as the multiplexing gain of the system, where the full cooperation is provided between the transmitters and/or between the receivers. Part three investigates the problem of fairness for a class of systems for which a subset of the capacity region, which includes the sum-capacity facets, forms a polymatroid structure. The main purpose is to find a point on the sum-capacity facet which satisfies a notion of fairness among active users. This problem is addressed in the cases where the complexity of achieving interior points is not feasible, and where the complexity of achieving interior points is feasible. In part four, $K$-user memoryless interference channels are considered; where each receiver sequentially decodes the data of a subset of transmitters before it decodes the data of the designated transmitter. A greedy algorithm is developed to find the users which are decoded at each receiver and the corresponding decoding order such that the minimum rate of the users is maximized. It is proven that the proposed algorithm is optimal. The results of the parts three and four are presented for general channels which include the multiple-antenna systems as special cases