Interference and Complexity Reduction in Multi-stage Multi-user Detection in DS-CDMA

Acquisition of PN sequences using multilayer perceptron neural network adaptive processor for multiuser detection in spread‐spectrum communication systems

“…Another important difference is that in the case of conventional detectors, the threshold is compared with the test cell content; while using the MLP‐NNAP detector, it is used for calculating the output value which can be translated into a decision. Therefore, the results of the learning process of the MLP‐NNAP detector are weights ( w hj , w 1 h ), and biases and b (which provide a CFAR). Now, the detector is operational and can be used in the test phase.…”

“…Code division multiple access (CDMA) is widely used in third‐generation cellular standards and is an access scheme for many future applications . One of the most important problems to be solved in direct sequence spread spectrum systems is the acquisition of pseudo noise (PN) sequences.…”

Multiuser detection: Comparative analysis of heuristic approach

“…This interference is the result of the random time offsets between signals, which make it impossible to design the code waveforms to be completely orthogonal (Moshavi, 1996). However, in CDMA systems multiple access interference (MAI) arises because of the non-ideal cross correlation properties of the spreading signals and multipath propagation (Ravindrababu et al, 2014). By reducing the interference it will gives the rise in capacity.…”

Quality of service differentiation in heterogeneous CDMA networks: a mathematical modelling approach

“…Recent advances in multicarrier CDMA (MC-CDMA) systems indicate good robustness against multipath propagation channels and high performance in terms of data transmission rates [11]. On the other hand, the radio resource planning and management in CDMA-based systems is a difficult task due to the multiple access interference (MAI), which is caused by both inter-and intra-cell mobile traffic [14,15]. This is especially true in a heterogeneous wireless environment with dense small cell deployments and an increasing number of end devices with dual connectivity [16].…”

“…..., r max and P (r) = 0 for r < 0, with lim r max →∞ r max r=0 As it is shown below in Subsection 4.2, j max is the state in which the local blockings LB t k,l (j) are practically equal to 1.4.2 Recursive Algorithm for the Calculation of State ProbabilitiesBelow we present our proposed algorithm for the calculation of state probabilities. The algorithm is based on the analysis presented in the previous subsection.S, D(s), T H s,d , tl t s,d , CL t maxPrecalculation determine each r t s,d from(14) and (15)Initialization 3:P (0) ← 1 4: ac t s,d (0) ← 0 5: ars t s,d (0) ← 0 RO(0|0) ← 1 7: LB t s,d (0) ← 0 While |1 − LB t s,d (r)| < ǫ do For c ∈ [1, ..., r] do17: determine RO(c|r) from (22) 18: determine LBP t s,d (c) from (24) and (25) End while 22: r max ← j The algorithm calculates the so-called un-normalized state probabilities, denoted bŷ P (r). It assigns an arbitrary (un-normalized) probability,P (0) = 1, to state r = 0 and, subsequently calculates all the probabilities in the while loop (lines 10-21).…”