Eckhard Ohlmer

5GNOW: Challenging the LTE Design Paradigms of Orthogonality and Synchronicity

LTE and LTE-Advanced have been optimized to deliver high bandwidth pipes to wireless users. The transport mechanisms have been tailored to maximize single cell performance by enforcing strict synchronism and orthogonality within a single cell and within a single contiguous frequency band. Various emerging trends reveal major shortcomings of those design criteria: (1) The fraction of machine-type-communications (MTC) is growing fast. Transmissions of this kind are suffering from the bulky procedures necessary to ensure strict synchronism. (2) Collaborative schemes have been introduced to boost capacity and coverage (CoMP), and wireless networks are becoming more and more heterogeneous following the non-uniform distribution of users. Tremendous efforts must be spent to collect the gains and to manage such systems under the premise of strict synchronism and orthogonality. (3) The advent of the Digital Agenda and the introduction of carrier aggregation are forcing the transmission systems to deal with fragmented spectrum. 5GNOW will question the design targets of LTE and LTE-Advanced having these shortcomings in mind. The obedience of LTE and LTE-Advanced to strict synchronism and orthogonality will be challenged. It will develop new PHY and MAC layer concepts being better suited to meet the upcoming needs with respect to service variety and heterogeneous transmission setups. A demonstrator will be built as Proof-of-Concept relying upon continuously growing capabilities of silicon based processing. Wireless transmission networks following the outcomes of 5GNOW will be better suited to meet the manifoldness of services, device classes and transmission setups being present in envisioned future scenarios like smart cities. The integration of systems relying heavily on MTC, e.g. sensor networks, into the communication network will be eased. The per-user experience will be more uniform and satisfying. To ensure this 5GNOW will contribute to upcoming 5G standardization.

Low Complexity GFDM Receiver Based on Sparse Frequency Domain Processing

Generalized frequency division multiplexing (GFDM) is a multi-carrier modulation scheme. In contrast to the traditional orthogonal frequency division multiplexing (OFDM), it can benefit from transmitting multiple symbols per sub-carrier. GFDM targets block based transmission which is enabled by circular pulse shaping of the individual sub- carriers. In this paper we propose a low complexity design for demodulating GFDM signals based on a sparse representation of the pulse-shaping filter in frequency domain. The proposed scheme is compared to receiver concepts from previous work and the performance is assessed in terms of bit error rates for AWGN and Rayleigh multipath fading channels. The results show, that for high-order QAM signaling, the error performance can be significantly improved with interference cancellation at reasonable computational cost.

Algorithm for Detecting the Number of Transmit Antennas in MIMO-OFDM Systems

In wireless MIMO-OFDM systems, knowledge of the channel between all transmit-receive antenna pairs is essential to enable the decoupling of spatial streams and coherent data detection at a receiver. Regarding a typical preamble design for MIMO channel estimation in an ad-hoc network, the preamble structure depends on the number of transmit antennas and this number must be known before the actual MIMO channel estimation is accomplished. In this work, we propose an algorithm to detect the number of transmit antennas, using only the received pilot sequences intended for MIMO channel estimation. Thus, no explicit signaling is needed, i.e. overhead and transmission latency can be reduced.

Field trial results for LTE-advanced concepts

Coordinated Multi-Point and relaying are two likely candidates for the upcoming LTE-Advanced standard, as both are able to satisfy the ever increasing demands for ubiquitous services with higher data rates. In this paper, we present field trial results for both techniques and discuss the most challenging problems during the implementation process in the EASY-C testbed in downtown Dresden.

Link Adaptation in Linearly Precoded Closed-Loop MIMO-OFDM Systems with Linear Receivers

Upcoming multi antenna systems such as 3GPP- LTE employ code book based multi-mode precoding in order to adapt to a wide range of channel conditions. Link adaptation, which includes the selection of precoding matrices, the number of spatially multiplexed layers as well as modulation coding schemes is a crucial task, carried out by the receiver. In this contribution we propose link adaption based on the measure of mutual information between the channel input and the linear detector output and evaluate the behavior of the proposed algorithm in spatially correlated and uncorrelated propagation scenarios. The results highlight the importance of proper link adaption in order to mitigate the impact of spatial correlation.

Urban Outdoor MIMO Experiments with Realistic Handset and Base Station Antennas

This work presents results for wireless outdoor MIMO transmission experiments at 2.68 GHz, which were conducted in an urban residential area, using realistic handset and base station antennas. Characteristic parameters of MIMO systems, obtained from measurements, were compared to theoretical results. From the comparison it could be concluded that the transmission of two spatial streams was well supported in the investigated 2 x 2 MIMO system, even with receive antenna element spacings as small as a quarter of the wave length. Comparing different receive antennas, the MIMO performance was found to be dominated by the received signal power rather than the spatial correlation.

Algorithm for Detecting the Number of Transmit Antennas in MIMO-OFDM Systems: Receiver Integration

Knowledge of the channel between all transmit-receive antenna pairs is essential for enabling the decoupling of spatial streams and coherent data detection in wireless MIMO-OFDM systems. The design of the preamble structure for MIMO channel estimation in an ad-hoc system depends on the number of transmit antennas in the system. A challenge at the receiver is therefore to accurately detect the number of transmit antennas in order to perform MIMO channel estimation. In this contribution we extend our previous algorithm for detecting the number of transmit antennas as presented in Ohlmer et al. (2008) and show how to integrate this algorithm in a typical receiver flow. Results show that our algorithm can be successfully applied in a realistic system if the unavoidable synchronization inaccuracies are carefully taken into account.

Model and comparative analysis of reduced-complexity receiver designs for the LTE-advanced SC-FDMA uplink ☆ ☆☆

Abstract Due to its favorable peak-to-average power ratio (PAPR), a single-carrier frequency-division multiple access (SC-FDMA) scheme has been chosen for the 3GPP Long Term Evolution Advanced (LTE-A) uplink, as opposed to the orthogonal frequency-division multiple access (OFDMA) scheme used in the downlink. SC-FDMA, however, is prone to suffer from the effects of inter-symbol interference. When combined with multiple-input multiple-output (MIMO) transmission, the complexity of optimal detection for SC-FDMA grows exponentially with the product of the number of transmitting antennas and the channel length. A means to reduce the complexity is to equalize the channel in the frequency domain first, similar to OFDMA, followed by detection in the time domain, using well-developed standard receivers for flat fading MIMO channels. Apparently, these reduced-complexity two-stage receivers suffer from a rate loss as a consequence of their simplifying design assumptions. In this paper, we provide an extensive model of SC-FDMA transmission with frequency domain equalization (FDE). Based on this model, we derive the achievable rates of four reduced-complexity two-stage receivers within the mismatched receiver framework in terms of generalized mutual information (GMI). The rate expressions allow us to assess the rate loss as compared to the optimal receiver for varying channel parameters such as channel length and spatial correlation. It is shown, for instance, that a distributed subcarrier mapping which is beneficial from a frequency diversity point of view substantially deteriorates the achievable rates. It is also explained how this loss can be compensated for by combining time-domain detection with frequency-domain interference cancelation.

Mutual Information of MIMO Transmission over Correlated Channels with Finite Symbol Alphabets and Link Adaptation

In this paper, results on the mutual information of MIMO transmission over spatially correlated channels in slow fading environments are presented. Different receiver techniques such as optimal maximum likelihood detection, parallel layer detection, successive interference cancelation detection and linear detection are compared. The transmit signals are derived from finite signal alphabets such as M-QAM. Different degrees of adapting the transmit signals to the channel state are taken into account. Results show that the gap between successive interference cancelation and maximum likelihood detection almost vanishes in a 2x2 MIMO transmission setup if link adaptation can be applied, regardless of spatial correlation.

Where to predict the channel for cooperative multi-cell transmission over correlated subcarriers?

In this work we discuss the aspect of channel prediction for cooperative multi-cell downlink transmission, where channel state information (CSI) of all users need to be available at all cooperating base stations (BSs). We assume that users feed CSI back to its local BS which forwards it to the other cooperating BSs using backhaul connections. In case of feedback and backhaul latency, CSI of a single user equipment (UE) is affected by multiple delays. Compensating for the delay via channel prediction raises the question of where to place the predictor. Prediction at the UE before the channel observations are quantized allows to compensate only for a single delay. Prediction at the BS side keeps the flexibility to compensate for the actual delay at each base station, at the drawback that less accurate information is available due to feedback quantization. This paper extends previous work from a transmission over uncorrelated subcarriers to the more realistic transmission over correlated subcarriers. Previously, we have shown that prediction before and after quantization results in the same channel uncertainty. As a consequence, prediction at the BS is always preferable if multiple delays need to be compensated. This paper shows that this result remains valid also for correlated subcarriers.