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Implementation of an Adaptive Design for the Iterative-MIMO Smart Sensor Detectors to Increase Energy Efficiency in Realistic Channel Conditions
Abstract
This paper investigates the adaptivity of the Fixed Sphere Decoder (FSD) algorithm, for iterative-multiple-input multiple-output (MIMO) detection in 4G LTE environment. The switching mechanism for the FSD depends on the calculated mutual information between the transmitters and receivers in real-time. The detector determines whether the receiver would detect the incoming symbols using a higher accuracy detector, a less performance detector or simply abandon further processing and reduce energy consumption by requesting a re-transmission. This paper provides the performance analysis for the proposed algorithm in realistic conditions by providing a detailed energy analysis of the algorithm for spatially correlated channel conditions. Analytical, simulation and implementation results show that the practical behavior of the proposed lterative-MIMO detector saves significant energy with a tolerable bit error rate performance degradation.
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Recently the use of lattice-reduction for signal detection in multiple antenna systems has been proposed. In combination with simple successive interference cancellation this scheme achieves near maximum-likelihood performance. To this end, the given MIMO channel is transformed into an almost orthogonal matrix leading to less noise enhancement within the detection. In this paper, we investigate the performance of common and lattice-reduction-aided detection schemes for correlated fading channels. We show, that the new scheme achieves significant gain in comparison to common algorithms. Thus, the new algorithm clearly outperforms existing methods with comparable complexity and is also more robust with respect to spatial correlation.
The signal detection algorithm of the vertical BLAST (Bell
Laboratories Layered Space-Time) wireless communications architecture is
briefly described. Using this joint space-time approach, spectral
efficiencies ranging from 20-40 bit/s/Hz have been demonstrated in the
laboratory under flat fading conditions at indoor fading rates. Early
results are presented
Theoretical and experimental studies of multiple-input/multiple-output (MIMO) radio channels are presented. A simple stochastic MIMO model channel has been developed. This model uses the correlation matrices at the mobile station (MS) and base station (BS) so that results of the numerous single-input/multiple-output studies that have been published in the literature can be used as input parameters. The model is simplified to the narrowband channels. The validation of the model is based upon data collected in both picocell and microcell environments. The stochastic model has also been used to investigate the capacity of MIMO radio channels, considering two different power allocation strategies, water filling and uniform and two different antenna topologies, 4×4 and 2×4. Space diversity used at both ends of the MIMO radio link is shown to be an efficient technique in picocell environments, achieving capacities within 14 b/s/Hz and 16 b/s/Hz in 80% of the cases for a 4×4 antenna configuration implementing water filling at a SNR of 20 dB.
In this paper, we first verify a previously proposed Kronecker-structure-based narrow-band model for nonline-of-sight (NLoS) indoor multiple-input-multiple-output (MIMO) radio channels based on 5.2-GHz indoor MIMO channel measurements. It is observed that, for the narrow-band case, the measured channel coefficients are complex Gaussian distributed and, consequently, we focus on a statistical description using the first- and second-order moments of MIMO radio channels. It is shown that the MIMO channel covariance matrix can be well approximated by the Kronecker product of the covariance matrices, seen from the transmitter and receiver, respectively. A narrow-band model for NLoS indoor MIMO channels is thus verified by these results. As for the wide-band case, it is observed that the average power-delay profile of each element of the channel impulse response matrix fits the exponential decay curve and that the Kronecker structure of the second-order moments can be extended to each channel tap. A wide-band MIMO channel model is then proposed, combining a simple COST 259 single-input-single-output channel model and the Kronecker structure. Monte Carlo simulations are used to generate indoor MIMO channel realizations according to the models discussed. The results are compared with the measured data using the channel capacity and good agreement is found.
In this paper, a comprehensive power performance analysis of a novel Adaptive Switching Algorithm for an iterative-MIMO system is investigated with the prime goal of minimizing energy consumption in the receiver. The algorithm works by switching between a high performance detection method, the Fixed Sphere Decoding, and a much lower complexity algorithm, the Vertical-Bell Laboratories Layered Space-Time Zero Forcing technique, controlled by a threshold according to the mutual information calculated during each transmission. Results show significant improvements over current non-adaptive receivers, where energy savings of more than 60% can be obtained using on the latest Xilinx®Virtex- 7 FPGA hardware.
This paper attempts to tackle one of the challenges faced in soft input soft output Multiple Input Multiple Output (MIMO) detection systems, which is to achieve optimal error rate performance with minimal power consumption. This is realized by proposing a new algorithm design that comprises multiple thresholds within the detector that, in real time, specify the receiver behavior according to the current channel in both slow and fast fading conditions, giving it adaptivity. This adaptivity enables energy savings within the system since the receiver chooses whether to accept or to reject the transmission, according to the success rate of detecting thresholds. The thresholds are calculated using the mutual information of the instantaneous channel conditions between the transmitting and receiving antennas of iterative-MIMO systems. In addition, the power saving technique, Dynamic Voltage and Frequency Scaling, helps to reduce the circuit power demands of the adaptive algorithm. This adaptivity has the potential to save up to 30% of the total energy when it is implemented on Xilinx®Virtex-5 simulation hardware. Results indicate the benefits of having this ‘intelligence’ in the adaptive algorithm due to the promising performance-complexity trade-off parameters in both software and hardware co-design simulation.
This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver. Inventing a codec architecture that can realize a significant portion of the great capacity promised by information theory is essential to a standout long-term position in highly competitive arenas like fixed and indoor wireless. Use (nT, nR) to express the number of antenna elements at the transmitter and receiver. An (n, n) analysis shows that despite the n received waves interfering randomly, capacity grows linearly with n and is enormous. With n = 8 at 1% outage and 21-dB average SNR at each receiving element, 42 b/s/Hz is achieved. The capacity is more than 40 times that of a (1, 1) system at the same total radiated transmitter power and bandwidth. Moreover, in some applications, n could be much larger than 8. In striving for significant fractions of such huge capacities, the question arises: Can one construct an (n, n) system whose capacity scales linearly with n, using as building blocks n separately coded one-dimensional (1-D) subsystems of equal capacity? With the aim of leveraging the already highly developed 1-D codec technology, this paper reports just such an invention. In this new architecture, signals are layered in space and time as suggested by a tight capacity bound.
We investigate the use of multiple transmitting and/or receiving antennas for single user communications over the additive Gaussian channel with and without fading. We derive formulas for the capacities and error exponents of such channels, and describe computational procedures to evaluate such formulas. We show that the potential gains of such multi-antenna systems over single-antenna systems is rather large under independenceassumptions for the fades and noises at different receiving antennas.
In this paper, we evaluate the performance of lattice reduction (LR) scheme in a highly correlated (2,2) channel where the receiver uses zero forcing V-BLAST as a detection algorithm. We also examine the behavior of the V-BLAST scheme with and without lattice reduction processing by comparing their symbol error rate (SER) with those resulting from sphere decoding (SD) when there is a spatial correlation coefficient up to 0.8 among receive antennas.
The use of multiple antennas at both transmitter and receiver is a promising technique for significantly increasing the capacity and spectral efficiency of wireless communication systems. In particular, spatial multiplexing techniques provide a means of increasing the data rate of the system without having to increase the transmitter power or the bandwidth. In recent years, special attention has been paid to the sphere decoder (SD) to detect spatially multiplexed signals. It provides optimal maximum likelihood (ML) performance with reduced complexity, compared to the maximum likelihood detector (MLD). An analysis of the performance of the SD in the presence of spatially correlated multiple-input multiple-output (MIMO) channels is presented. Analytical and simulation results show that, compared to suboptimal linear and nonlinear MIMO detectors, the SD suffers a complexity increase when correlation exists between the antennas at the transmitter or the receiver. In addition, a novel low-complexity channel ordering technique is introduced to reduce the complexity of the SD
A new detection algorithm for uncoded multiple input-multiple output (MIMO) systems based on the complex version of the sphere decoder (SD) is presented in this paper. It performs a fixed number of operations during the detection process, overcoming the two main problems of the SD from an implementation point of view: its variable complexity and its sequential nature. The algorithm combines a novel channel matrix ordering with a search through a very small subset of the complete transmit constellation. A geometrically-based method is used to study the effect the proposed ordering has on the statistics of the MIMO channel. Using those results, a generalization is given for the structure this subset needs to follow in order to achieve quasi-maximum likelihood (ML) performance. Simulation results show that it has only a very small bit error rate (BER) degradation compared to the original SD while being suited for a fully-pipelined hardware implementation due to its low and fixed complexity.
Evidence that the 'Kronecker' model underestimates the channel capacity of an 8×8 multiple input, multiple output (MIMO) system in indoor non-line-of-sight (NLOS) scenarios is presented. Moreover, the model does not render the multipath structure correctly, which is the cause for the systematic capacity mismatch.
We investigate the effects of fading correlations in multielement
antenna (MEA) communication systems. Pioneering studies showed that if
the fades connecting pairs of transmit and receive antenna elements are
independently, identically distributed, MEAs offer a large increase in
capacity compared to single-antenna systems. An MEA system can be
described in terms of spatial eigenmodes, which are single-input
single-output subchannels. The channel capacity of an MEA is the sum of
capacities of these subchannels. We show that the fading correlation
affects the MEA capacity by modifying the distributions of the gains of
these subchannels. The fading correlation depends on the physical
parameters of MEA and the scatterer characteristics. In this paper, to
characterize the fading correlation, we employ an abstract model, which
is appropriate for modeling narrow-band Rayleigh fading in fixed
wireless systems
This paper applies random matrix theory to obtain analytical characterizations of the capacity of correlated multiantenna channels. The analysis is not restricted to the popular separable correlation model, but rather it embraces a more general representation that subsumes most of the channel models that have been treated in the literature. For arbitrary signal-to-noise ratios (SNR), the characterization is conducted in the regime of large numbers of antennas. For the low- and high-SNR regions, in turn, we uncover compact capacity expansions that are valid for arbitrary numbers of antennas and that shed insight on how antenna correlation impacts the tradeoffs among power, bandwidth, and rate.
Rayleigh fading channels in mobile digital communication systems Part I: characterization
- B Sklar
On the robustness of lattice-reduction aided detectors in correlated MIMO
- D Wubber
- V Kulm
- K D Kammeyer