Abstract--Location area (LA) planning plays an important role in cellular networks because of the trade-off caused by paging and registration signaling. The upper bound on the size of an LA is the service area of a mobile switching center (MSC). In that extreme case, the cost of paging is at its maximum, but no registration is needed. On the other hand, if each cell is an LA, the paging cost is minimal, but the registration cost is the largest. In general, the most important component of these costs is the load on the signaling resources. Between the extremes lie one or more partitions of the MSC service area that minimize the total cost of paging and registration. In this paper, we try to find an optimal method for determining the location areas. For that purpose, we use the available network information to formulate a realistic optimization problem. We propose an algorithm based on simulated annealing (SA) for the solution of the resulting problem. Then, we investigate the quality of the SA technique by comparing its results to greedy search and random generation methods.

Consumer demand profiles and fluctuating renewable power generation are two main sources of uncertainty in matching demand and supply. This paper proposes a model of the electricity market that captures the uncertainties on both the operator and user sides. The system operator (SO) implements a temporal linear pricing strategy that depends on real-time demand and renewable generation in the considered period combining real-time pricing with time-of-use pricing. The announced pricing strategy sets up a noncooperative game of incomplete information among the users with heterogeneous, but correlated consumption preferences. An explicit characterization of the optimal user behavior using the Bayesian Nash equilibrium solution concept is derived. This explicit characterization allows the SO to derive pricing policies that influence demand to serve practical objectives, such as minimizing peak-to-average ratio or attaining a desired rate of return. Numerical experiments show that the pricing policies yield close to optimal welfare values while improving these practical objectives.Index Terms-Demand response management (DRM), game theory, renewable energy.

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Robust single-user detection is employed in a direct sequence code-division multiple-access (DS-CDMA) system in which the noise process contains impulsive components. The breakdown point is computed for a mixture noise model. The bit error probability expressions are derived under a Gaussian mixture. The performance is also evaluated in the presence of power imbalance and asynchronous reception. Noise, rather than interference, is shown to be the primary obstacle in achieving good performance for certain practical signal power and user load levels. It is concluded that DS-CDMA employing a robust correlator receiver performs better than the conventional matched filter in an impulsive noise environment.

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