Mobile Multiuser Detection Technique

In mobile / cellular networks the multiuser detection technology emerged in early 80s. it is now developed in to an important full-fledged field in multi-access communication. In the conventional single user detector in DS-CDMA system, MAI and near-far effect cause limitation of capacity. On the other hand the optimal MUD suffers from computational complexity that grows exponentially with number active user. During a last two decade there has been a lot of interest of sub optimal multiuser detector which are low in complexity but deliver negotiable performance. This topic highlighted various detection techniques. As in Multiuser MIMO system a base station equipped with multiple antennas serves a number of users. Conventionally the communication between the BS and the user is performed by orthogonalizing the channel so that the BS communicates with each user in separate time frequency resources. This is not optimal from an information theoretic point of view and high rate can be obtained, if the BS communicates with several users in same time frequency response. DOI: 10.17762/ijritcc2321-8169.15082

Multiuser Detection by MAP Estimation with Sum-of-Absolute-Values Relaxation

In this article, we consider multiuser detection that copes with multiple access interference caused in star-topology machine-to-machine (M2M) communications. We assume that the transmitted signals are discrete-valued (e.g. binary signals taking values of $\pm 1$), which is taken into account as prior information in detection. We formulate the detection problem as the maximum a posteriori (MAP) estimation, which is relaxed to a convex optimization called the sum-of-absolute-values (SOAV) optimization. The SOAV optimization can be efficiently solved by a proximal splitting algorithm, for which we give the proximity operator in a closed form. Numerical simulations are shown to illustrate the effectiveness of the proposed approach compared with the linear minimum mean-square-error (LMMSE) and the least absolute shrinkage and selection operator (LASSO) methods.Comment: submitted; 6 pages, 7 figure

Compressive Sensing for Spread Spectrum Receivers

With the advent of ubiquitous computing there are two design parameters of wireless communication devices that become very important power: efficiency and production cost. Compressive sensing enables the receiver in such devices to sample below the Shannon-Nyquist sampling rate, which may lead to a decrease in the two design parameters. This paper investigates the use of Compressive Sensing (CS) in a general Code Division Multiple Access (CDMA) receiver. We show that when using spread spectrum codes in the signal domain, the CS measurement matrix may be simplified. This measurement scheme, named Compressive Spread Spectrum (CSS), allows for a simple, effective receiver design. Furthermore, we numerically evaluate the proposed receiver in terms of bit error rate under different signal to noise ratio conditions and compare it with other receiver structures. These numerical experiments show that though the bit error rate performance is degraded by the subsampling in the CS-enabled receivers, this may be remedied by including quantization in the receiver model. We also study the computational complexity of the proposed receiver design under different sparsity and measurement ratios. Our work shows that it is possible to subsample a CDMA signal using CSS and that in one example the CSS receiver outperforms the classical receiver.Comment: 11 pages, 11 figures, 1 table, accepted for publication in IEEE Transactions on Wireless Communication