[ Interference Cancellation: III. A Signal Subspace Perspective ]

[ Interference Cancellation: IV. A Blind Receiver Design Perspective ]

**Introduction**

Interference cancellation provides a promising alternative to the conventional or optimum detectors in multiuser detection. Interference cancellation methods typically require less implementation complexity while practically o ering similar performance. The idea behind interference cancellation is to estimate the multiple access and/or multipath induced interference and then to subtract the interference estimate from the received signal. Hence, compared to other multiuser detection schemes, interference cancellation pays more attention on the estimation of the multiple access interference (MAI). Different schemes for the MAI estimation lead to different interference cancellation schemes. Actually, interference cancellation detector will cancel the interfering signal exactly provided that the decision was correct and channel information is known. Otherwise it will double the contribution of the interferers. The main alternatives for implementation of interference cancellation are parallel hard interference cancellation (PIC) and serial/successive hard interference cancellation (SIC), while many other variants on these basic principles have also been developed. With conventional PIC, all user are simultaneously demodulated and detected in a parallel behave. With conventional SIC, a decision for the symbol of the stronger user is made rst, the interference from this user is subsequently removed in the the next stronger user's receiver before the next user's receiver make its decision and so on.

On this blog, we consider a synchronous DS/CDMA system and review the principles of interference cancellation. several soft interference cancellation schemes, including direct interference cancellation detector, MAME interference cancellation detector and MMSE interference detector, are introduced with di fferent MAI estimation schemes. I show that, besides MAME interefence cancellation, the proposed direct interference cancellation detector has the same performance of the classic decorrelating detector while the MMSE multiuser detection and the MMSE interference cancellation actually are the same detectors.

**System Model**

Figure 1. Multiuser Detection System Model |

We consider a single-cell synchronous DS/CDMA model and assume that there are K active users in the cell, the data { b

_{k}[n]: k = 1, 2, ..., K } of these K users are individually spread using the corresponding spreading sequences { c_{k}= [c_{1k}c_{2k}... c_{Lck}]^{T}: k = 1, 2, ..., K; } with the spreading gain L_{c}and synchronously received from these users through multipath channel and corrupted additive white Gaussian noise (AWGN) with the variance ¾2 n [3]. The channel is a multipath channel with up to P resolvable paths and corrupted by AWGN. The baseband representation of the received signal due to user k is given byr

_{k}(t) = Σ

_{p=1}

^{P}α

_{pk}A

_{k}[n]b

_{k}[n]c

_{k}(t-nT-τ

_{p}) + n

_{k}(t)

where α

_{pk}is the gain of the pth path of user k’s signal and b_{k}[n] is the nth bit sent by user k. We assume that the { b_{k}[n] : k = 1, 2, . . . , K } are independent and identically distributed random variables with E{b_{k}[i]} = 0 and E|b_{k}[i]|^{2}= 1. The parameters {c_{k}(t) : k = 1, 2, . . . , K} denote the normalized spreading signal waveform of K users during the interval [0, T] and {A_{k}[n] : k = 1, 2, . . . , K} are the signal amplitudes at time t = nT. Without loss of generality, the P propagation delays from the base station to user k are ordered such that 0 ≤ τ_{1}≤ τ_{2}≤ . . . ≤ τ_{P}.At the receiver side, the received signal passes through chip-matched filter (CMF) φ (t) and then RAKE combiner. The combined output r (t) is

r (t) = A

_{1}b

_{1}c

_{1}(t − nT − τ

_{1}) ⊗ φ (t − τ

_{1}) + m

_{ISI}(t) + m

_{MAI}(t) + n (t)

Figure 2. A typical matrix representation of conventional multiuser detection system model |

**Interference Cancellation**

Figure 3. The block structure of a basic interference cancellation detector. |

As in Figure 3, it shows that there are usually two basic stages in interference cancellation realization. At the fi rst stage, the MAI from other users are reconstructed. At the second stage, the MAI is removed from the received signal and the nal decision is made from the rest signal through a matched lter. Thus, the key part in interference cancellation is how to estimate MAI as effciently as possible.

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