Abstract:
Method and apparatus embodiments are provided for low complexity message passing algorithm (MPA) detection with substantially minor or tolerated performance loss compared to the standard MPA. A method includes calculating, at a detector, a plurality of function nodes (FNs) according to a plurality of received multiplexing signals for a one or a plurality of user equipments (UEs) using a plurality of first MPA computations that map a plurality of variable nodes (VNs) corresponding to the UEs to the FNs and using a priori information in an initial vector of probabilities for each of the VNs, excluding from the first MPA computations a plurality of first relatively small multiplication terms, updating the probabilities for the VNs using the last calculated FNs and a plurality of second MPA computations that map the FNs to the VNs, and excluding a plurality of second relatively small multiplication terms from the second MPA calculations.
Abstract:
A method embodiment includes implementing, by a base station (BS), a grant-free uplink transmission scheme. The grant-free uplink transmission scheme defines a first contention transmission unit (CTU) access region in a time-frequency domain, defines a plurality of CTUs, defines a default CTU mapping scheme by mapping at least some of the plurality of CTUs to the first CTU access region, and defines a default user equipment (UE) mapping scheme by defining rules for mapping a plurality of UEs to the plurality of CTUs.
Abstract:
An embodiment method includes receiving, by a first user equipment (UE), a message, for a second UE, transmitted over a plurality of resource blocks (RBs) on behalf of a communications controller and determining a plurality of log-likelihood ratios (LLRs) in accordance with the received plurality of RBs. The method also includes transmitting, a subset of the determined LLRs to the second UE.
Abstract:
User equipment (UE) cooperation can be improved by relaying partial soft information to target UEs. More specifically, a cooperating UE may relay a subset of log-likelihood ratios (LLRs) to the target UE. The subset of LLRs may correspond to fewer than all resource blocks of the original transmission. This may allow UE cooperation to be effective when the cooperating UE was only able to decode a portion of the original transmission. This may also allow fewer network resources (e.g., bandwidth, etc.) to be used when the target UE does not need all of the soft information to decode the original transmission. Multiple cooperating UEs can provide different subsets of LLRs, and the subsets may or may not overlap with one another.
Abstract:
User equipment (UE) cooperation can be improved by relaying partial soft information to target UEs. More specifically, a cooperating UE may relay a subset of log-likelihood ratios (LLRs) to the target UE. The subset of LLRs may correspond to fewer than all resource blocks of the original transmission. This may allow UE cooperation to be effective when the cooperating UE was only able to decode a portion of the original transmission. This may also allow fewer network resources (e.g., bandwidth, etc.) to be used when the target UE does not need all of the soft information to decode the original transmission. Multiple cooperating UEs can provide different subsets of LLRs, and the subsets may or may not overlap with one another.
Abstract:
A method for generating a codebook includes applying a unitary rotation to a baseline multidimensional constellation to produce a multidimensional mother constellation, wherein the unitary rotation is selected to optimize a distance function of the multidimensional mother constellation, and applying a set of operations to the multidimensional mother constellation to produce a set of constellation points. The method also includes storing the set of constellation points as the codebook of the plurality of codebooks.
Abstract:
Virtualized group-wise communications between a wireless network and a plurality of user equipments (UEs) are supported using UE cooperation. UE cooperation includes receiving, at a cooperating UE (CUE), downlink information from the wireless network destined for a target UE (TUE) and associated with a group identifier (ID). The group ID indicates a virtual multi-point (ViMP) node that includes the TUE and the CUE. The UE cooperation also includes sending the downlink information to the TUE. The UE or UE component can have a processor configured to forward between the wireless network and a TUE at least some information that is associated with a group ID indicating a ViMP node that groups the TUE and the UE.
Abstract:
Embodiments are provided for a compress and forward relaying scheme in joint multi-cell processing. A plurality of base stations receive similar combinations of user signals from a plurality of users, compress the signals using quantization, and relay the signals over respective backhaul links to a processor in the network for decoding the signal. The processor determines suitable quantization noise levels for the backhaul links according to a weighted sum-rate maximization function for optimizing the quantization noise levels, subject to a backhaul sum capacity constraint on the backhaul links. The determined quantization noise levels are sent to the base stations, which then quantize the received combinations of user signals according to the quantization noise levels and relay the quantized signals to the processor. The quantization is according to a Wyner-Ziv coding or a single user compression algorithm that excludes statistical correlations between the user signals at the base stations.
Abstract:
Method and apparatus are provided for transmission of data. A precoder is selected, and a feedforward filter is derived in accordance with the precoder. In some embodiments, the precoder is an arbitrary effective precoder. Data prepared using the precoder and the feedforward filter can then be transmitted.
Abstract:
Embodiments are provided for a compress and forward relaying scheme in joint multi-cell processing. A plurality of base stations receive similar combinations of user signals from a plurality of users, compress the signals using quantization, and relay the signals over respective backhaul links to a processor in the network for decoding the signal. The processor determines suitable quantization noise levels for the backhaul links according to a weighted sum-rate maximization function for optimizing the quantization noise levels, subject to a backhaul sum capacity constraint on the backhaul links. The determined quantization noise levels are sent to the base stations, which then quantize the received combinations of user signals according to the quantization noise levels and relay the quantized signals to the processor. The quantization is according to a Wyner-Ziv coding or a single user compression algorithm that excludes statistical correlations between the user signals at the base stations.