List-Based Detector and Access Points Selection in Cell-Free Massive MIMO Using LDPC Codes

Abstract

This paper proposes a cell-free massive multipleinput multiple-output (CF-mMIMO) architecture with joint listbased detection with soft interference cancelation (soft-IC) and access points (APs) selection. In particular, we derive a new closed-form expression for the minimum mean-square error receive filter while taking the uplink transmit powers and APs selection into account. This is achieved by optimizing the receive combining vector by minimizing the mean square error between the detected symbol estimate and transmitted symbol, after canceling the multi-user interference (MUI). By using low-density parity check (LDPC) codes, an iterative detection and decoding (IDD) scheme based on a message passing is devised. In order to perform joint detection at the central processing unit (CPU), the access points locally estimate the channel and send their received sample data to the CPU via the front haul links. In order to enhance the system's bit error rate performance, the detected symbols are iteratively exchanged between the joint detector and the LDPC decoder in log likelihood ratio form. Furthermore, we draw insights into the derived detector as the number of IDD iterations increase. Finally, the proposed list detector is compared with existing detection techniques.

Centralized and Decentralized IDD Schemes for Cell-Free Massive MIMO Systems: AP Selection and LLR Refinement

“…The index of UE k that uses the same pilot is denoted as t k ∈ {1, ..., τ p } with ϑ k ⊂ {1, ..., K } as the subset of UEs that use the same pilot as UE k inclusive. The complex received signal at the l-th AP after the UE transmission, [1], [2], [33] Y l , with dimensions N × τ p , is given by…”

“…The dynamic cooperative clustering (DCC) approach described in [2], [33] is considered when selecting the APs. Unlike existing approaches for APs-Sel, the proposed approach incorporates the APs-Sel in the receive filter expression, which facilitates its computation.…”

“…The receiver consists of an MMSE filter followed by a soft interference cancellation scheme, which may use either a successive or a list-based successive interference cancellation technique. The receiver first creates soft estimates of the transmitted symbols by computing the jth UE symbol mean sj based on the soft beliefs from the LDPC decoder [13], [32], [33] given E {s j } = sj as described by sj = s∈A sP(s j = s), (8) where A is the set of complex constellations. The a-priori probability of the extrinsic LLRs is given by [32], [33]…”

“…The receiver first creates soft estimates of the transmitted symbols by computing the jth UE symbol mean sj based on the soft beliefs from the LDPC decoder [13], [32], [33] given E {s j } = sj as described by sj = s∈A sP(s j = s), (8) where A is the set of complex constellations. The a-priori probability of the extrinsic LLRs is given by [32], [33]…”

“…where Λ i (b i ) is the extrinsic LLR of the i-th bit calculated by the LDPC decoder from the previous iteration, and s bl ∈ (+1, −1) denotes the l-th bit of symbol s. The variance of the j-th UE symbol is calculated as [32], [33]…”