Abstract-Joint power control and beamforming schemes are proposed for cellular systems where adaptive arrays are used only at base stations. In the uplink, mobile powers and receiver diversity combining vectors at base stations are calculated jointly. The mobile transmitted power is minimized, while the signal-tointerference-and-noise ratio (SINR) at each link is maintained above a threshold. A transmit diversity scheme for the downlink is also proposed where the transmit weight vectors and downlink power allocations are jointly calculated such that the SINR at each mobile is above a target value. The proposed algorithm achieves a feasible solution for the downlink if there is one and minimizes the total transmitted power in the network. In a reciprocal network it can be implemented in a decentralized system, and it does not require global channel response measurements. In a nonreciprocal network, where the uplink and downlink channel responses are different, the proposed transmit beamforming algorithm needs to be implemented in a centralized system, and it requires the knowledge of the downlink channel responses. The performances of these algorithms are compared with previously proposed algorithms through numerical studies.Index Terms-Adaptive arrays, downlink beamforming, power control, transmit beamforming.

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We develop an algorithm to reconstruct the wavelet coefficients of an image from the Radon transform data. The proposed method uses the properties of wavelets to localize the Radon transform and can be used to reconstruct a local region of the cross section of a body, using almost completely local data that significantly reduces the amount of exposure and computations in X-ray tomography. The property that distinguishes our algorithm from the previous algorithms is based on the observation that for some wavelet bases with sufficiently many vanishing moments, the ramp-filtered version of the scaling function as well as the wavelet function has extremely rapid decay. We show that the variance of the elements of the null-space is negligible in the locally reconstructed image. Also, we find an upper bound for the reconstruction error in terms of the amount of data used in the algorithm. To reconstruct a local region 16 pixels in radius in a 256x256 image, we require 22% of full exposure data.

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Abstract-Recently, there has been considerable interest in using antenna arrays in wireless communication networks to increase the capacity and decrease the cochannel interference. Adaptive beamforming with smart antennas at the receiver increases the carrier-to-interference ratio (CIR) in a wireless link. This paper considers a wireless network with beamforming capabilities at the receiver which allows two or more transmitters to share the same channel to communicate with the base station. The concrete computational complexity and algorithm structure of a base station are considered in terms of a software radio system model, initially with an omnidirectional antenna. The software radio computational model is then expanded to characterize a network with smart antennas. The application of the software radio smart antenna is demonstrated through two examples. First, traffic improvement in a network with a smart antenna is considered, and the implementation of a hand-off algorithm in the software radio is presented. The blocking probabilities of the calls and total carried traffic in the system under different traffic policies are derived. The analytical and numerical results show that adaptive beamforming at the receiver reduces the probability of blocking and forced termination of the calls and increases the total carried traffic in the system. Then, a joint beamforming and power control algorithm is implemented in a software radio smart antenna in a CDMA network. This shows that, by using smart antennas, each user can transmit with much lower power, and therefore the system capacity increases significantly.Index Terms-Adaptive beamforming, handoff, power control, smart antennas, software radio.