Characterization of effective capacity in antenna selection MIMO systems

This chapter is attempted to provide a survey of the advanced concepts and related issues involved in Multiple Input Multiple Output (MIMO) systems. MIMO system technology has been considered as a really significant foundation on which to build the next and future generations of wireless networks. The chapter addresses advanced MIMO techniques such as polarization diversity and antenna selection. We gradually provide an overview of the MIMO features from basic to more advanced topics. The first sections of this chapter start by introducing the key aspects of theMIMO theory. TheMIMO systemmodel is first presented in a genericway. Then, we proceed to describe diversity schemes used in MIMO systems. MIMO technology could exploit several diversity techniques beyond the spatial diversity. These techniques essentially cover frequency diversity, time diversity and polarization diversity. We further provide the reader with a geometrically based models for MIMO systems. The virtue of this channel modeling is to adopt realisticmethods for modeling the spatio-temporal channel statistics from a physical wave-propagation viewpoint. Two classes for MIMO channel modeling will be described. These models involve the Geometry-based Stochastic ChannelModels (GSCM) and the Stochastic channel models. Besides the listedMIMO channel models already described, we derive and discuss capacity formulas for transmission over MIMO systems. The achieved MIMO capacities highlight the potential of spatial diversity for improving the spectral efficiency of MIMO channels. When Channel State Information (CSI) is available at both ends of the transmission link, the MIMO system capacity is optimally derived by using adaptive power allocation based on water-filling technique. The chapter continues by examining the combining techniques for multiple antenna systems. Combining techniques are motivated for MIMO systems since they enable the signal to noise ratio (SNR) maximization at the combiner output. The fundamental combing techniques are the Maximal Ratio Combining (MRC), the Selection Combining (SC) and the Equal Gain Combining(EGC). Once the combining techniques are analyzed, the reader is introduced to the beamforming processing as an optimal strategy for combining. The use of multiple antennas significantly improves the channel spectral efficiency. Nevertheless, this induces higher system complexity of the communication system and the communication system performance is effected due to correlation between antennas that need to be deployed at the same terminal. As such, the antenna selection algorithm for MIMO systems is presented. To elaborate on this point, we introduce Space time coding techniques for MIMO systems and we evaluate by simulation the performance of the communication system. Next, we emphasis on multi polarization techniques for MIMO systems. As a background, we presume that the reader has a thorough understanding of antenna theory. We recall the basic antenna theory and concepts that are used throughout the rest of the chapter. We rigorously introduce the 3D channel model over the Non-Line of Sight (NLOS) propagation channel for MIMO system with polarized antennas. We treat the depolarization phenomena and we study its effect on MIMO system capacity. The last section of the chapter provides a scenario for collaborative sensor nodes performing distributed MIMO system model which is devoted to sensor node localization in Wireless Sensor Networks. The localization algorithm is based on beamforming processing and was tested by simulation. Our chapter provides the reader by simulation examples for almost all the topics that have been treated for MIMO system development and key issues affecting achieved performance.

In this letter, we propose two different joint transmit and receive antenna subset selection schemes for multiple-input multiple-output (MIMO) systems on the basis of capacity maximization criterion. We assume that perfect channel state information (CSI) is known at the receiver but unknown to the transmitter. As the selection signaling is perfectly fed back to the transmitter, we propose a flexible two-step selection algorithm (TSSA) in practical MIMO channel scenarios. Computer simulations show that TSSA can maximize the capacity at low computation cost in most scenarios. It performs well in terms of capacity, computational complexity and flexibility. Furthermore, we propose a simplified algorithm based on the correlation matrix when the channel correlation information (CCI) is known to the transmitter. Simulation results show that the proposed correlation matrix based selection algorithm is only slightly inferior to an optimal selection algorithm.

In this paper, we propose the supervised learning classifier (SLC) based transmit antenna selection (TAS) for spatial modulation (SM) multiple-input multiple-output (MIMO) system. Firstly, the classical Euclidean distance based antenna selection (EDAS) method is investigated. Secondly, we convert the typical TAS problem into a classification problem and propose a low complexity multi-output classifier design. Then, two SLC schemes, random forest decision (RFD) and deep neural network (DNN) with adaptive momentum (ADAM) optimization, are employed to solve the TAS problem. Numerical results illustrate that the proposed DNN based TAS (DNN-TAS) scheme obtains better average bit error rate (ABER) performance than the RFD based TAS (RFD-TAS) scheme and outperforms the typical TAS methods with much lower complexity. Moreover, the proposed DNN-TAS scheme achieves the suboptimal ABER performance at high signal-to-noise ratio (SNR) region compared with the optimal high complexity EDAS algorithm.

We analyze the asymptotic performance of rate adaptation for Transmit Antenna Selection (TAS) and Maximum Eigenmode Beamforming (MEB) schemes in Multiple-Input Multiple-Output (MIMO) systems under imperfect channel state information (CSI) and feedback delay. The rate is adapted according to a target outage probability. We derive lower and upper bounds to this rate. We also asymptotically characterize the multi-step prediction error when MMSE prediction is used to combat feedback delay. Using the bounds and the prediction error asymptotics, we show that the rate gap from the ideal CSI scenario asymptotically grows logarithmically with SNR. The slope is at most the target outage probability. We find that when the target outage probability is decreased faster than an identified growth rate and prediction error goes to zero, then the rate gap remains bounded.

The research work in this dissertation addresses reduced complexity equalization technique for multipath channels with large delay spread. This has been one of the key challenges for high data rate impulse radio based Ultra-Wideband (UWB) communication systems using low cost receiver design. Our research focus is on developing efficient and effective tap selection techniques for non-uniformly spaced Minimum Mean Squared Error (MMSE) equalization and applying it to UWB systems to achieve high performance with reduced receiver complexity. In this dissertation, a new class of tap selection techniques based on Order Recursive Least Squares (ORLS) and Matching Pursuit (MP) algorithms is proposed for UWB multipath channel equalization in the presence of Inter Symbol Interference (ISI) and unknown co-channel interference. The proposed tap selection techniques are directly implemented based on training symbol sequence under Least Squares (LS) criterion without the need for explicit channel estimation. In addition, Diagonal Loading (DL) technique is incorporated into the tap selection and MMSE equalization processes to insure system robustness given limited number of training symbols in the case of practical implementation. The proposed tap selection based equalizer is shown to outperform the conventional uniformly spaced linear equalizer and is with reduced computational complexity. The LS based technique proposed for equalizer tap selection is then extended to receive antenna selection for high data rate UWB systems with multiple receive antenna elements to achieve improved performance in the presence of Narrow Band Interference (NBI). Based on the LS criterion, antenna selection techniques for Multiple Input Multiple Output (MIMO) systems are also explored in our research work. Novel transmit and receive antenna selection techniques are proposed for MIMO spatial multiplexing systems with linear receivers under LS criterion. Unlike conventional approaches, xii

Orbital Angular Momentum (OAM) has been considered as a new dimension in wireless transmission. In Multiple Input Multiple Output (MIMO) system, OAM can also be utilized as the new Degrees of Freedom (DoF) to manipulate the beamforming instead of the traditional Channel State Information (CSI) feedback, so that the computation complexity of the beamforming dramatically decreases, as well as the capacity of the transmission is maintained approaching the upper bound of the MIMO system. For example, this beamforming manipulation with OAM is extremely efficient in the Line of Sight (LoS) MIMO system. In this paper, the mathematical model of the DoF in beamforming manipulation in MIMO with OAM is established. The computation complexity is evaluated, and compared in LoS environment within MIMO, MIMO-OAM, and OAM. The quantitatively simulation confirms the fact that MIMO-OAM has the best trade-off between the capacity and the computation complexity, which gives a consolidated evidence that the MIMOOAM scheme can be adopted as an efficient beamforming scheme in LoS backhaul links between the base station and the self backhaul small cell station, or Near Field Communications (NFC) directly between mobile terminals. Due to these promising applications, MIMO-OAM may become one of the candidate technologies in Beyond 5G (B5G) mobile communications.

In this paper, the bit error rate (BER) performance of multiuser multiple-input multiple-output (MIMO) systems over Rayleigh fading channels is studied, and corresponding asymptotic performance is analyzed. Based on the asymptotic analysis at high signal to noise ratio (SNR), using the probability density functions (PDF) of the instantaneous channel power gain, the diversity gain and coding gain of the system with transmit antenna selection (TAS) scheme and space-time block coding (STBC) scheme are derived, respectively. As a result, the same full diversity gain is achieved for two transmission schemes, but their coding gains are different. With the obtained diversity gain and coding gain, the asymptotic BER expressions for two transmission schemes are respectively derived, which are in good agreement with the corresponding simulation results. The results show that the multiuser MIMO system with TAS scheme has better BER performance than that with STBC scheme due to higher coding gain.

Euclidean distance optimized antenna selection (EDAS) has proven to be able to achieve high transmit diversity gains for spatial modulation (SM) multiple-input multiple-output (MIMO) systems, but the exhaustive search over all possible antenna subsets may result in an intractable search complexity, especially for large-scale MIMO (LS-MIMO) systems. In this paper, a novel EDAS-equivalent criterion, relaying on matrix dimension reduction, is proposed to reduce the search complexity. Based upon this criterion, for small-scale SM-MIMO systems, a pair of transmit antenna selection (TAS) schemes, namely, the tree search based antenna selection (TSAS), and the decremental antenna selection (D-AS) schemes, are developed. Specifically, the TSAS scheme works by iteratively splitting the original Euclidean distance (ED) matrix into submatrices with smaller dimensions. TSAS achieves the same bit error rate (BER) performance as that of the exhaustive search at the cost of exponential search complexity. To address this issue, D-AS is carried out by excluding one specific transmit antenna from all the possible candidates in each iteration based on the channel information. D-AS is able to offer a near-optimal BER performance with a further reduction in terms of the search complexity. Moreover, we extend the D-AS scheme to LS-SM-MIMO systems by sorting all the ED elements with the low-complexity heapsort algorithm. Our simulation results show that the proposed D-AS algorithm outperforms conventional TAS schemes conceived for LS-SM-MIMO systems.

In this paper, transmit antenna selection (TAS) is applied to space shift keying (SSK) modulation to obtain diversity gain. The receiver selects a transmit antenna subset in each transmission block according to the channel state information (CSI) and sends the subset index to the transmitter through feedback. Several antenna selection schemes are evaluated for SSK from perspectives of performance, feedback overhead and complexity. A greedy transmit antenna selection scheme is proposed to reduce the computation complexity, which shows almost the same performance as exhaustive search. In the special case that the number of active antennas equals two, an antenna selection scheme with one transmit antenna fixed (Fix-1 scheme) is proposed to reduce the amount of feedback, whose exact bit error ratio (BER) performance is derived. Through asymptotic BER analysis we show that Fix-1 scheme has the same diversity order as exhaustive search.

This letter considers the effect of channel estimation errors on the performance of space-time coded (STC) systems with transmit and receive antenna selection over quasi-static flat fading channels. By performing pairwise error probability analysis and presenting numerical examples, we show that the diversity order achieved with perfect channel state information (CSI) is still achievable with imperfect CSI used both at the antenna selection and the space-time decoding processes. We note that our results apply to general STC systems with both transmit and/or receive antenna selection based on largest received powers which can be estimated by any channel estimator.

We propose a precoder design to minimize the codeword error rate of multiple-input multiple-output (MIMO) systems in the presence of channel estimation errors. Our proposed scheme only requires knowledge of the second-order statistics of the channel, noise and the estimation errors; an estimate of the instantaneous channel state information (CSI) is not required. Compared to the instantaneous CSI requirement, our assumption is more practical since obtaining an accurate CSI is challenging if the channel fluctuates rapidly, while the channel statistics are likely to remain unchanged for a much longer period. Furthermore, the feedback overhead from the receiver to the transmitter is greatly reduced. When compared to the case without transmit preceding, our proposed design achieves a significant improvement in error performance: (i) for a real 2 × 2 MIMO system with 4-PAM modulation and at codeword error rate of 104, our proposed precoder design achieves coding gains of up to 6 dB and (ii) for a real 4 × 4 MIMO system with BPSK modulation and at codeword error rate of 104, coding gains of up to 6.5 dB can be achieved.

In this paper, we present a comprehensive performance analysis of multiple-input multiple-output (MIMO) systems with transmit antenna selection (TAS) and stochastic power allocation (SPA) for the spatially correlated fading channels. Two best transmit antennas that maximize the instantaneous received signal-to-noise (SNR) are selected to transmit the Alamouti scheme and maximal-ratio combining (MRC) is applied at the receiver. With correlation matrices available to the transmitter, SPA is applied on these selected antennas. Two different methods are given to derive the explicit upper bounds on the bit-error rate (BER) performance. Finally we present numerical results to verify our analysis. It is shown that the TAS/SPA scheme can achieve high performance in spatially correlated channels.

SUMMARYAlthough there are many research results for the keyhole fading channels in the current literature, fewer results have investigated the antenna selection scheme and quantified the diversity order. In this letter, we first derive some simple statistics of the output signal‐to‐noise ratio for the orthogonal space–time block coding over keyhole fading channels. On the basis of these results, we derive an approximate BER expression for the keyhole MIMO channels with receive antenna selection scheme. Results show that the diversity order with receive antenna selection is min{nR,nT}for nR ≠ nT, which means that the full diversity order with antenna selection is maintained. Finally, numerical results demonstrate the accuracy of our analytical expressions and the tightness of approximate formulas. Copyright © 2012 John Wiley & Sons, Ltd.

This paper presents a comprehensive analysis of the outage probability for multiple-input-multiple-output (MIMO) systems with receive antenna selection. In this analysis, it is assumed that 1) for a given M receive antennas, the receiver selects the best L antennas that maximize the capacity, 2) the channel state information is perfectly known at the receiver, but not at the transmitter, 3) the subchannels fade independently, and 4) the fading coefficients change very slowly such that averaging with respect to these coefficients is not possible. Under these assumptions, two upper bounds on the outage probability with receive antenna selection are derived. The first bound is used to show that the diversity order is maintained with antenna selection. The second bound is used to approximate the degradation in signal-to-noise ratio due to antenna selection. Furthermore, the asymptotic behavior of the outage probability for MIMO systems is analyzed as the number of transmit antennas tends to infinity. The asymptotic results presented are extended to the case with receive antenna selection. For all cases, explicit expressions for the threshold for the outage probability are derived. Several numerical examples that validate the analysis are also presented

This paper studies the performance of transmit antenna selection algorithms in spatially correlated fading MIMO channels. The antenna subset is selected based on maximizing the channel capacity. A novel method is proposed to select the optimum set of transmit antennas based on the upper bound on the mean channel capacity. The proposed method based only on the fading correlation and not the instantaneous channel realization. And also its computational complexity is low and tends to be realized. The simulation results show that antenna selection of transmitter can increase the channel capacity of MIMO system by 1 bit/s in a flat fading environment with a rank deficient channel.