Variance Of Multiple Access Interference Research Articles

Performance Comparison between MAI and Noise Constrained LMS Algorithm for MIMO CDMA DFE and Linear Equalizers

This paper presents a performance comparison between a constrained least mean squared algorithm for MIMO CDMA decision feedback equalizer and linear equalizer. Both algorithms are constrained on the length of spreading sequence, number of users, variance of multiple access interference as well as additive white Gaussian noise (new constraint). An important feature of both algorithms is that multiple access interference together with noise variance is used as a constraint in MIMO CDMA linear and decision feedback equalization systems. Convergence analysis is performed for algorithm in both cases. From the simulation results shown at the end show that algorithm developed for decision feedback equalizer has outperformed the algorithm developed for linear equalizer in MIMO CDMA case

Multiple-Access Interference Plus Noise-Constrained Least Mean Square (MNCLMS) Algorithm for CDMA Systems

Since multiuser code-division multiple-access (CDMA) communications systems suffer significantly from multiple-access interference (MAI) and from classical white Gaussian noise, it is therefore necessary to consider their impact on the performance of these systems. It is well known that the learning speed of any adaptive filtering algorithm is increased by adding a constraint to it. In this paper, a constrained least-mean-square (LMS) algorithm, which incorporates the knowledge of the number of users, spreading sequence length, and additive noise variance, is developed subject to the new combined constraint comprising the MAI and noise variance for a synchronous downlink direct-sequence CDMA system. The novelty of this constraint resides in the fact that the MAI variance was never used as a constraint. In our approach, a Robbins-Monro algorithm is used to minimize the conventional mean-square-error criterion subject to the variance of the new constraint (MAI plus noise). This constrained optimization technique results in an (MAI plus noise)-constrained LMS (MNCLMS) algorithm. The MNCLMS algorithm is a type of variable step-size LMS algorithm where the step-size rule arises naturally from the constraints on MAI and noise variance. Convergence and tracking analysis of the proposed algorithm are carried out in the presence of MAI. Finally, a number of simulations are conducted to compare the performance of the MNCLMS algorithm with other adaptive algorithms.

Performance and Optimization of Multistage Partial Parallel Interference Cancellation for Wideband CDMA Systems in Multipath Fading Channels

In this paper, a closed-form bit error rate (BER) of hard-decision multistage partial parallel interference cancellation (PPIC) having perfect and imperfect channel estimation for complex spreading code-division multiple access (CDMA) over multipath Rayleigh channels was derived. The effects of receiving BER, power ratio of pilot to data channels, multiple-access interference (MAI) and multipath interference, additive white Gaussian noise, and other factors affecting channel estimation error are analyzed. The expression determining the optimal interference cancellation weight at path level for PPIC is first derived. Then, the oscillatory behavior of user-level-optimized PIC and the convergence of perfect channel estimation PIC and path-level-optimized PIC are validated. Results indicate that all factors determining the optimal weight certainly affect the BER performance of PPIC and that the lower BER limit of multistage PPIC depends on the adjustable factors, which include power ratio, observation length, and signal-to-noise ratio, and an unchangeable factor, i.e., number of users. In addition, the variance of MAI for complex spreading sequence is obtained, and the analytical expression can also be employed to predict the performance of multicode CDMA

Performance analysis of MC-CDMA in Rayleigh fading channels with correlated envelopes and phases

The performance analysis of a multicarrier code division multiple access (MC-CDMA) system in Rayleigh fading channels with correlated envelopes and phases is presented, and the effect of phase correlation on the bit error rate (BER) performance is demonstrated. An equivalence relation between independent phases and random spreading sequences for asynchronous MC-CDMA is established, which can explain why the problem of code-independent variance of multiple access interference (MAI) has appeared in the past. Furthermore, it is found that the interference from other subcarriers is always less than half the interference from the same subcarriers for asynchronous MC-CDMA with random spreading sequences. It is also found that Gold, orthogonal Gold, Walsh and random sequences yield similar BER performance in an asynchronous MC-CDMA system with a relatively large number of users. For an uplink MC-CDMA, time synchronisation does not improve BER performance significantly. Finally, asynchronous MC-CDMA systems benefit from the increase of delay spread of the channel, while the opposite conclusion holds for the downlink of MC-CDMA.

Variances of multiple access interferencecode average against data average

The average interference parameter (AIP) introduced by Pursley (1977) has been discussed as a measure of bit error probabilities in asynchronous DS/CDMA systems. It is shown that the AIP is a variance of multiple access interference (MAI) with respect to data symbols, and that a variance of MAI with respect to code symbols gives bit error probabilities if spread-spectrum code sequences are generated by Markov information sources. Pursley's even and odd cross-correlation functions are reexamined.

TCM/SSMA communication systems with cascaded sequences and PAM/QAM signal sets

An expression in matrix form for the multiple-access interference (MAI) in an asynchronous direct-sequence spread-spectrum multiple-access (DS/SSMA) communication system with cascaded sequences (CVs), arbitrary chip waveforms, and trellis-coded modulation (TCM) with a pulse amplitude modulation (PAM) or quadrature amplitude modulation (QAM) signal set is obtained. TCM provides significant coding gain while the CVs decrease the correlation between the MAI of adjacent data intervals. The expression is used to calculate arbitrarily accurate probability density functions (PDFs) of the MAI in the TCM system and to derive an accurate approximation of the MAI variance. It also helps illustrate some properties of the MAI by separating contributing parameters into different matrices. We derive an approximation of the upper union bound on the bit-error probability and investigate its applicability. The results show that CV schemes can greatly reduce the pairwise error probabilities (PEPs) until the length of the CV becomes greater than that of the error weight sequence (EWS) under consideration.