Asynchronous cooperative communication systems: A survey on signal designs

Abstract

Cooperative communications is a promising technique for future high speed wireless communications. These systems may be formulated as virtual multi-input multi-output (MIMO) systems where spatial/cooperetive diversity is a key advantage. However, different from MIMO systems, one of the major challenges for cooperative communications systems is that the cooperative transmissions in cooperative systems may be neither time nor frequency synchronized, since the transmissions are from multiple cooperative nodes at different locations. The existing signal designs for co-located MIMO systems may not be able to collect the cooperative diversity in cooperative communications systems. This paper gives an overview of recent research efforts on combating the time and frequency asynchronism of the cooperative communication network. We focus on the signal designs (or space-time codings/modulations) to achieve full cooperative diversity, and summarize some of the resent distributed space-timing coding and space-frequency coding techniques to combat timing errors and frequency offsets, and in the meantime to achieve full cooperative diversity, in both one-way and two-way cooperative networks.

Transceiver Design for Distributed STBC Based AF Cooperative Networks in the Presence of Timing and Frequency Offsets

“…2 + LN − 1 is the computational complexity to evaluate the objective function χ in (16). Note that extensive simulations demonstrate that the proposed DE algorithm on average converges to the true estimates after approximately D I = 220 and D I = 530 iterations for K = 2 and K = 4, respectively, for a wide range of SNRs.…”

“…Remark 2: Even though the general conditions for global convergence of evolutionary algorithms are established in [48], it cannot be analytically shown that DE meets these conditions [49] and converges to the global solution of (16). Moreover, in [48], no specific algorithm that meets these conditions is proposed.…”

“…The computational complexity of the LS algorithm, denoted by C LS is calculated as given by (20) at the bottom of this page, where κ τ and κ ν denote the step sizes or resolutions for timing and frequency offsets, respectively, in the exhaustive search in (16) and C α = 2K 3 + (4LN − 1)K 2 + (LN − 1)K is the complexity for obtainingα via (15).…”

“…Note that this comparison is carried out by evaluating the LS estimates using exhaustive search in (16) and by setting L = 80, κ τ = 10 −2 , κ ν = 10 −4 , D P = 20K, D R = 0.9, D F = 0.85, and D I = 220 and 530 for K = 2 and K = 4, respectively. These values are selected to ensure that both estimators reach the CRLB over a wide range of SNR values.…”

“…It has been shown that time asynchronism can destroy the elaborate structure of the DSTBCs, reducing the achievable diversity gain [14], [15]. Similarly, carrier frequency asynchronism can lead to a symbol to symbol channel time variation and to a violation of the essential requirement for successful DSTBC decoding and achieving spatial diversity [16].…”