Cognitive code-division multiplexing and cooperative networking
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The objective of this work is to investigate the problem of cognitive/adaptive code-division multiplexing and cooperative networking. Along this line, our work can be divided into the following subjects: ( i ) We developed a novel Binary Signature Design Algorithm which returns the binary signature vector, that maximizes the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum-SINR filter, near arcs of least SINR decrease from the real maximum SINR solution in the Euclidean vector space, in the presence of disturbance and multipath fading channels. The quality of the proposed adaptive binary designs was measured against theoretical upper bound of the complex/real eigenvector maximizer and some existing signature assignment schemes. ( ii ) We studied the performance of our Binary Signature Design Algorithm when applied to collaborative relay networks. We evaluated numerically and by simulations the bit error rate (BER) and outage probability of cooperative wireless transmissions under several basic decode-and-forward relay network architectures. ( iii ) We considered the problem of scaling upwards overloaded minimum total-squared-correlation (TSC) binary signature sets and proposed a novel design procedure cognitively/adaptively search the binary signature for the new signal in the system that lies near the continuous-valued arcs of least TSC increase, given a min-TSC overloaded set ( K, L ) where K > L . The quality of the new binary signature design was tested directly against the Karystinos-Pados TSC bound. ( iv ) We considered the problem of multiuser data hiding in transform-domain hosts (images, in particular, herein) and identified the orthonormal signature set that offers maximum sum SINR embedding for any fixed embedding amplitude values. We showed that the set is also sum capacity optimal in terms of bits per multiuser embedding under the assumption that the transform-domain host data are Gaussian. When there is flexibility in assigning amplitudes across users under a total host distortion constraint, we derived the user amplitude values that meet the total constraint and further maximize sum capacity. ( v ) We analyzed the multiuser signature assignment problem with the criterion of sum-SINR/sum-capacity adaptive maximization with K users signatures under control, in the presence of disturbance and noise. We also discussed the special case of underloaded system of individual SINR maximization.