Digital video broadcasting (DVB-C2) and other modern communication standards increase diversity by means of a symbol-level interleaver that spans over several codewords. De-interleaving at the receiver requires a large memory, which has a significant impact on the implementation cost. In this paper, we propose a technique that reduces the de-interleaver memory size. By quantizing log-likelihood ratios with bit-specific quantizers and compressing the quantized output, we can significantly reduce the memory size with a negligible increase in computational complexity. Both the quantizer and compressor are designed via a GMI-based maximization procedure. For a typical DVB-C2 scenario, numerical results show that the proposed solution enables a memory saving up to 30%.

The problem of maximizing a utility function while limiting the outage probability below an appropriate threshold is investigated. A coded-division multi access wireless network under mixed Nakagami-lognormal fading is considered. Solving such a utility maximization problem is difficult because the problem is non-convex and non-geometric with mixed integer and real decision variables and no explicit functions of the constraints are available. In this paper, three methods for the solution of the utility maximization problem are proposed. By the first method, a simple explicit outage approximation is used and the constraint that rates are integers is relaxed yielding a standard convex programming optimization that can be solved quickly but at the price of a reduced accuracy. The second method uses a more accurate outage approximation, which allows one solving the utility maximization problem by the Lagrange duality for non-convex problems and contraction mapping theory. The third method is a combination of the first and the second one. Numerical results show that the first method performs well for average values of the outage requirements, whereas the second one is always more accurate, but is also more computationally expensive. Finally, the third method gives same accuracy as the second one, but has a lower computational complexity only for a small number of transmitters.

In an OFDM system using pilots for channel estimation, time interpolation among pilots of different OFDM symbols is commonly used to improve the estimate. The estimated channel impulse response may be also windowed to further reduce noise and disturbances. However, for a transmission over a time-varying channel, suboptimal time interpolation, implemented with a filter having only a few taps not matched to the maximum Doppler frequency, degrades channel estimation. In this paper we provide an analysis of the effects of pilot time interpolation over time-varying channels. We show in particular that suboptimal time interpolation yields aliases in the estimated channel impulse response and we derive a closed-form expression of the aliases¿ variance. As aliases can lead to an erroneous estimate of channel length and consequent errors in windowing, we propose a technique to detect aliases and correct the channel length estimate. Parameters of the detection techniques are optimized by an analysis that provides closed-form expressions of the false alarm and miss detection probabilities. Numerical results show the merits of the proposed techniques in a mobile transmission of the terrestrial digital video broadcasting standard (DVB-T).

A radio power control strategy to achieve maximum throughput for the up-link of CDMA wireless systems with variable spreading factor is investigated. The system model includes slow and fast fading, rake receiver, and multi-access interference caused by users with heterogeneous data sources. The quality of the communication is expressed in terms of outage probability, while the throughput is defined as the sum of the users' transmit rates. The outage probability is accounted for by resorting to a lognormal approximation. A mixed integer-real optimization problem P1, where the objective function is the throughput under outage probability constraints, is investigated. Problem P1is solved in two steps: firstly, we propose a modified problem P2to provide feasible solutions, and then the optimal solution is obtained with an efficient branch-and-bound search. Numerical results are presented and discussed to assess the validity of our approach.

The problem of maximizing the sum of the transmit rates while limiting the outage probability below an appropriate threshold is investigated for networks where the nodes have limited processing capabilities. We focus on CDMA wireless network whose rates are characterized under mixed Rayleigh- lognormal fading. The outage probability is given implicitly by a complex function so that solving the optimization problem requires substantial computing. In this paper, we propose a novel explicit approximation of this function that allows solving the problem in an affordable manner. We propose two solutions of the maximization problem with the simplified outage probability constraint: one solves the problem using mixed integer-real programming. The other relaxes the constraints that rates be integers yielding a standard convex programming optimization that can be solved much faster. Numerical results show that our approaches perform well for average values of the outage requirements.

We characterize the maximum throughput achievable for the up-link of a power-controlled WCDMA wireless system with variable spreading factor. Our system model includes multi access interference caused by users with heterogeneous data sources, and quality of service expressed in terms of outage probability. Inner loop and outer loop power control mechanisms are also explicitly taken into account. We express the system throughput as the sum of the users transmission rates, and propose a mixed integer optimization program where the objective function is the sum of the rates under outage probability constraints. Then, we solve the optimization problem proposing an efficient optimal approach based on two steps: firstly, a modified problem provides feasible solutions, and then the optimal solution is obtained with branch and bound criteria. Numerical results confirm the validity of our approach, and show how the throughput depends on the power control fluctuation, activity of the sources, and quality of service.

We study the downlink of a system with multiple antennas at the base stations and propose two different schemes for admission control and beamforming selection when a new user enters the system. To keep the complexity low, only the power control, not the spatial signatures of beamformers for the already admitted users, are adjusted. Numerical examples illustrate the performance compared to joint optimization of all users