The channel estimation techniques for OFDM systems based on pilot arrangement are investigated. The channel estimation based on comb type pilot arrangement is studied through different algorithms for both estimating channel at pilot frequencies and interpolating the channel. The estimation of channel at pilot frequencies is based on LS and LMS while the channel interpolation is done using linear interpolation, second order interpolation, low-pass interpolation, spline cubic interpolation, and time domain interpolation. Time-domain interpolation is obtained by passing to time domain through IDFT (Inverse Discrete Fourier Transform), zero padding and going back to frequency domain through DFT (Discrete Fourier Transform). In addition, the channel estimation based on block type pilot arrangement is performed by sending pilots at every sub-channel and using this estimation for a specific number of following symbols. We have also implemented decision feedback equalizer for all sub-channels followed by periodic block-type pilots. We have compared the performances of all schemes by measuring bit error rate with 16QAM, QPSK, DQPSK and BPSK as modulation schemes, and multi-path Rayleigh fading and AR based fading channels as channel models.

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In this paper, we present an algorithm for routing in wireless ad hoc networks using information about geographical location of the nodes. We assume each node knows its geographical position and the position of the node to which it wants to send a packet. Initially, the nodes only know their neighbors but over time they discover other nodes in the network. The routing table at a node S is a list hp i ; S i i where p i is a geographical position and S i is a neighbor of node S. When node S receives a packet for a node D at position posD, it finds the p i in its routing table which is closest to posD and forwards the packet to the neighbor S i. We prove the correctness of the algorithm and show that our algorithm naturally aggregates the nodes so that the routing table sizes are of size O L n logn, where L n is the mean route discovery path length, and n is the number of nodes. We also present methods for taking positional errors, node failures and mobility into account. We justify the results through simulation.

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