Capacity-achieving probability measure for a reduced number of signaling points

Putting bounding constraints on the input of a channel leads in many cases to a discrete capacity-achieving distribution with a finite support. Given a finite number of signaling points, we determine reduced subsets and the corresponding optimal probability measures to simplify the receiver design. The objective for the subset selection is to keep the channel quality high by maximizing mutual information and cutoff rate. Two approaches are introduced to obtain a capacity-achieving probability measure for the reduced subset. The first one is based on a preceded signaling point selection while the second one chooses the signaling points and corresponding probabilities simultaneously. Numerical results for both approaches show that using only a small number of signaling points achieves a very high mutual information compared to channels utilizing the full set of signaling points.     

Integrated Optimal Cell Site Selection and Frequency Allocation for Cellular Radio Networks

Two major planning problems are encountered when designing a cellular radio network. The initial question is where to locate the base transmitter stations such that full coverage is achieved at low interference. This is relevant for frequency division (FDMA) as well as code division multiple access (CDMA) technology. If the locations of base stations are given, then for an FDMA-system frequencies have to be assigned such that there is a sufficient number of channels per cell available at a low total interference level. Since cell site selection and frequency allocation have mutual influences on each other, the ultimate goal is to deal with both problems in a single design step. The main intention of this paper is to model the above planning issues as linear integer programs, and to discuss solution methods for the corresponding NP-hard problems. According to their increasing complexity we proceed from channel allocation via cell site selection to an integrated single setup.     

Optimal Base Station Positioning and Channel Assignment for 3G Mobile Networks by Integer Programming

In this paper, discrete mathematical programming approaches are used to solve the frequency allocation and cell site selection problem in an integrated setup. Both CDMA (code division multiple access) and FD/TDMA (frequency/time division multiple access) technologies will be important for 3rd generation mobile systems. If all users share the same bandwidth, base transmitter stations should be placed such that a maximum of traffic can be carried at low interference rates. The expected traffic is represented by spatially scattered weighted nodes. The problem to select an optimal set of base station locations from a given pool of configurations is formulated as an integer linear program and solved by combinatorial optimization methods. For systems which employ FD/TDMA schemes, the cell site optimization process depends on the assignment of channels. We suggest an integrated linear programming approach to solve both objectives in a single planning step. Because of the problems' tremendous complexity, special branch-and-bound procedures are developed as exact and approximate solution methods. An examples is given for a typical urban scenario with base transmitters below roof tops.