Bandwidth efficient multi-station wireless streaming based on complete complementary sequences

Data streaming from multiple base stations to a client is recognized as a robust technique for multimedia streaming. However the resulting transmission in parallel over wireless channels poses serious challenges, especially multiple access interference, multipath fading, noise effects and synchronization. Spread spectrum techniques seem the obvious choice to mitigate these effects, but at the cost of increased bandwidth requirements. This paper proposes a solution that exploits complete complementary spectrum spreading and data compression techniques jointly to resolve the communication challenges whilst ensuring efficient use of spectrum and acceptable bit error rate. Our proposed spreading scheme reduces the required transmission bandwidth by exploiting correlation among information present at multiple base stations. Results obtained show 1.75 Mchip/sec (or 25%) reduction in transmission rate, with only up to 6 dB loss in frequency-selective channel compared to a straightforward solution based solely on complete complementary spectrum spreading

Orthogonal Multiple Access with Correlated Sources: Feasible Region and Pragmatic Schemes

In this paper, we consider orthogonal multiple access coding schemes, where correlated sources are encoded in a distributed fashion and transmitted, through additive white Gaussian noise (AWGN) channels, to an access point (AP). At the AP, component decoders, associated with the source encoders, iteratively exchange soft information by taking into account the source correlation. The first goal of this paper is to investigate the ultimate achievable performance limits in terms of a multi-dimensional feasible region in the space of channel parameters, deriving insights on the impact of the number of sources. The second goal is the design of pragmatic schemes, where the sources use "off-the-shelf" channel codes. In order to analyze the performance of given coding schemes, we propose an extrinsic information transfer (EXIT)-based approach, which allows to determine the corresponding multi-dimensional feasible regions. On the basis of the proposed analytical framework, the performance of pragmatic coded schemes, based on serially concatenated convolutional codes (SCCCs), is discussed

Models, Statistics, and Rates of Binary Correlated Sources

This paper discusses and analyzes various models of binary correlated sources, which may be relevant in several distributed communication scenarios. These models are statistically characterized in terms of joint Probability Mass Function (PMF) and covariance. Closed-form expressions for the joint entropy of the sources are also presented. The asymptotic entropy rate for very large number of sources is shown to converge to a common limit for all the considered models. This fact generalizes recent results on the information-theoretic performance limit of communication schemes which exploit the correlation among sources at the receiver.Comment: submitted for publicatio