Optimum Detection of Code Division Multiplexed Signals

Decision feedback multiuser detection: a systematic approach

“…Therefore, it is easily shown that (27) Substituting (25) and (27) into (24) yields the bit error probability of the D-DFD as - (28) The asymptotic effective energy corresponding to each product of -function terms in the double summation in (28) is Since the term corresponding to the slowest exponential rate of decay dominates the error probability as , we have that the asymptotic effective energy of user is - (29) Equations (28) and (29) give exact formulas for the BER and AEE of the D-DFD. Note, however, that the properties of the AEE's of the D-DFD obtained in [43], i.e., the bounds of (21) and the equalities in (22) and (23) may be tedious to derive by using of the exact formula for AEE in (29).…”

“…The conditional error probabilities in (25) and (27) are no longer computable because the conditioning on past decisions alters the distribution of the additive noise in the current decision statistic (from prior to posterior) in a way that is difficult to characterize analytically (see [36]). A different approach is necessary.…”

“…Meanwhile, the simple decorrelating detectors of Lupas and Verdú [20] (see also Schneider [27]) for coherent detection and Varanasi and Aazhang [38] for differentially coherent detection were obtained by optimizing near-far resistance among linear and bilinear detectors, respectively. Near-far resistance is defined as the worst asymptotic efficiency over all the interfering users' energies for coherent detection and over complex amplitudes for differentially coherent reception.…”

The Behaviour of Vertical Bell Laboratories Layered Space-Time Algorithm Combined with Multiuser Detection Schemes in Wireless Communication System

“…Thus, CDMA performance can be greatly enhanced by multiuser receivers which compensate for MAI. One of the first investigations into multiuser reception of CDMA signals was presented in [9].…”

A Near-Maximum-Likelihood Decoding Algorithm for MIMO Systems Based on Semi-Definite Programming

“…However, unfortunately, these algorithms usually result in a noticeable degradation in the performance. Examples of such polynomial time algorithms include: Zero Forcing Detector (ZFD) [6], [7], Minimum Mean Squared Error Detector (MMSED) [8], [9], Decision Feedback Detector (DFD) and Vertical Bell Laboratories Layered Space-Time Nulling and Cancellation Detector (VBLAST Detector) [10], [11].…”