14 research outputs found

    Bounds on the Sum Capacity of Synchronous Binary CDMA Channels

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    In this paper, we obtain a family of lower bounds for the sum capacity of Code Division Multiple Access (CDMA) channels assuming binary inputs and binary signature codes in the presence of additive noise with an arbitrary distribution. The envelope of this family gives a relatively tight lower bound in terms of the number of users, spreading gain and the noise distribution. The derivation methods for the noiseless and the noisy channels are different but when the noise variance goes to zero, the noisy channel bound approaches the noiseless case. The behavior of the lower bound shows that for small noise power, the number of users can be much more than the spreading gain without any significant loss of information (overloaded CDMA). A conjectured upper bound is also derived under the usual assumption that the users send out equally likely binary bits in the presence of additive noise with an arbitrary distribution. As the noise level increases, and/or, the ratio of the number of users and the spreading gain increases, the conjectured upper bound approaches the lower bound. We have also derived asymptotic limits of our bounds that can be compared to a formula that Tanaka obtained using techniques from statistical physics; his bound is close to that of our conjectured upper bound for large scale systems.Comment: to be published in IEEE Transactions on Information Theor

    Hierarchy Based Construction of Signature Matrices for Simplified Decoding in Overloaded CDMA

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    The overloaded CDMA system, as the solution to the capacity limit of its conventional counterpart, has drawn frequent interest of the researchers in the past. While there exists numerous proposals on the construction of uniquely decodable (UD) signature matrices for overloaded CDMA system with very high value of overloading factor, most of them lag the efficient multiuser detector (MUD) for noisy transmission. Here, by efficient, we imply the MUD to have acceptable BER performance and simplified in design. Whereas the lack of efficiency of several MUDs is primarily due to the impact of excess level of multiple access interference (MAI) because of the rise in the number of active users, its random nature prohibits its accurate estimation and elimination. Under such constraints, if the signature matrices can be intelligently constructed so as to generate a defined and controlled pattern (hierarchy) of MAI so that the designed MUD will exploit the knowledge of this hierarchy to remove the MAI completely and attain better error performance at much lower cost of complexity. We consider this as the motivation for research in this thesis. First, we propose the ternary signature matrix with orthogonal subsets (TSMOS), where the matrix with index-k comprises of k orthogonal subsets with each having different number signatures, and all subsets besides the first (largest) one are of ternary type. The correlation (interference) pattern among the signatures is mapped into a twin tree hierarchy, which is further leveraged to design a simplified MUD using the linear decoding blocks like matched filter (MF) to provide errorfree and better error performance for noiseless and noisy transmission respectively. Next, we generalize the construction of TSMOS to multiple structures i.e.; Type I, Type II, Type III and mixed versions and reveal the complementary feature of 50% signatures of the largest (binary) subset that further results in their optimality. Further, we propose the non-ternary version of SMOS (called as 2k-SMOS), where the binary alphabets in each of the k subsets are different from each other. With vii no complementary feature, 50% signatures of its largest subset are also found to be optimal. The superiority of 2k-SMOS over TSMOS is also verified for an overloading capacity of 150%. Next, we propose and discuss the hybrid SMOS (HSMOS), where the subsets from TSMOS and 2k-SMOS are used as the constituents to produce multiple SMOS structures, of which TSMOS and 2k-SMOS are treated as the special cases. For better understanding of the features of the whole family of SMOS (with an overloading capacity of 200%), the gradual change in the twin tree hierarchy and BER performance of the left and right child of the individual subsets are studied. Similar to SMOS, we also introduce the hierarchy based low density signature (HLDS) matrix, where any UD matrix satisfying particular criterion can be considered as the basis set. For hadamard matrix as the basis set, we design a MUD that uses the MF to implement the decision vector search (DVS) algorithm, which is meant to exploit the advantageous hierarchy of constellation of the transmitted vector to offer errorfree decoding. For noisy channel, the marginal degradation in the level of BER of the MUD (DVS) as compared to the optimum joint maximum likelihood decoder (MLD) is worthy to be overlooked when compared with the significant gain achieved in terms of complexity. For the smallest dimension of the hadamard matrix as the basis, the MUD is further simplified to offer recovery using a comparison driven decision making algorithm, also known as comparison aided decoding (CAD). Despite simplicity, the error performance of the MUD (CAD) is observed to be very close to that of MUD (DVS)

    Code design based on metric-spectrum and applications

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    We introduced nested search methods to design (n, k) block codes for arbitrary channels by optimizing an appropriate metric spectrum in each iteration. For a given k, the methods start with a good high rate code, say k/(k + 1), and successively design lower rate codes up to rate k/2^k corresponding to a Hadamard code. Using a full search for small binary codes we found that optimal or near-optimal codes of increasing length can be obtained in a nested manner by utilizing Hadamard matrix columns. The codes can be linear if the Hadamard matrix is linear and non-linear otherwise. The design methodology was extended to the generic complex codes by utilizing columns of newly derived or existing unitary codes. The inherent nested nature of the codes make them ideal for progressive transmission. Extensive comparisons to metric bounds and to previously designed codes show the optimality or near-optimality of the new codes, designed for the fading and the additive white Gaussian noise channel (AWGN). It was also shown that linear codes can be optimal or at least meeting the metric bounds; one example is the systematic pilot-based code of rate k/(k + 1) which was proved to meet the lower bound on the maximum cross-correlation. Further, the method was generalized such that good codes for arbitrary channels can be designed given the corresponding metric or the pairwise error probability. In synchronous multiple-access schemes it is common to use unitary block codes to transmit the multiple users information, especially in the downlink. In this work we suggest the use of newly designed non-unitary block codes, resulting in increased throughput efficiency, while the performance is shown not to be substantially sacrificed. The non-unitary codes are again developed through suitable nested searches. In addition, new multiple-access codes are introduced that optimize certain criteria, such as the sum-rate capacity. Finally, the introduction of the asymptotically optimum convolutional codes for a given constraint length, reduces dramatically the search size for good convolutional codes of a certain asymptotic performance, and the consequences to coded code-division multiple access (CDMA) system design are highlighted
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