Network efficiency enhancement by reactive channel state based allocation scheme

Now a day the large MIMO has considered as the efficient approach to improve the spectral and energy efficiency at WMN. However, the PC is a big issue that caused by reusing similar pilot sequence at cells, which also restrict the performance of massive MIMO network. Here, we give the alternative answer, where each of UEs required allotting a channel sequences before passing the payload data, so as to avoid the channel collision of inter-cell. Our proposed protocol will ready to determine the channel collisions in distributed and scalable process, however giving unique properties of the large MIMO channels. Here we have proposed a RCSA (Reactive channel state based allocation) scheme, which will very productively work with the RAP blockers at large network of MIMO. The position of time-frequency of RAP blocks is modified in the middle of the adjacent cells, because of this design decision the RAP defend from the hardest types of interference at inter-cell. Further, to validate the performance of our proposed scheme it will be compared with other existing technique

Soft Pilot Reuse and Multi-Cell Block Diagonalization Precoding for Massive MIMO Systems

The users at cell edge of a massive multiple-input multiple-output (MIMO) system suffer from severe pilot contamination, which leads to poor quality of service (QoS). In order to enhance the QoS for these edge users, soft pilot reuse (SPR) combined with multi-cell block diagonalization (MBD) precoding are proposed. Specifically, the users are divided into two groups according to their large-scale fading coefficients, referred to as the center users, who only suffer from modest pilot contamination and the edge users, who suffer from severe pilot contamination. Based on this distinction, the SPR scheme is proposed for improving the QoS for the edge users, whereby a cell-center pilot group is reused for all cell-center users in all cells, while a cell-edge pilot group is applied for the edge users in the adjacent cells. By extending the classical block diagonalization precoding to a multi-cell scenario, the MBD precoding scheme projects the downlink transmit signal onto the null space of the subspace spanned by the inter-cell channels of the edge users in adjacent cells. Thus, the inter-cell interference contaminating the edge users' signals in the adjacent cells can be efficiently mitigated and hence the QoS of these edge users can be further enhanced. Our theoretical analysis and simulation results demonstrate that both the uplink and downlink rates of the edge users are significantly improved, albeit at the cost of the slightly decreased rate of center users.Comment: 13 pages, 12 figures, accepted for publication in IEEE Transactions on Vehicular Technology, 201

Low-complex Bayesian estimator for imperfect channels in massive muti-input multi-output system

Motivated by the fact that the complexity of the computations is one of the main challenges in large multiple input multiple output systems, known as massive multiple-input multiple-output (MIMO) systems, this article proposes a low-complex minimum mean squared error (MMSE) Bayesian channel estimator for uplink channels of such systems. First, we have discussed the necessity of the covariance information for the MMSE estimator and how their imperfection knowledge can affect its accuracy. Then, two reduction phases in dimension and floating-point operations have been suggested to reduce its complexity: in phase 1, eigenstructure reduction for channel covariance matrices is implemented based on some truncation rules, while in phase 2, arithmetic operations reduction for matrix multiplications in the MMSE equation is followed. The proposed procedure has significantly reduced the complexity of the MMSE estimator to the first order O(M), which is less than that required for the conventional MMSE with O(M3) in terms of matrix dimension. It has been shown that the estimated channels using our proposed procedure are asymptotically aligned and serve the same quality as the full-rank estimated channels. Our results are validated by averaging the normalized mean squared error (NMSE) over a length of 500 sample realizations through a Monte Carlo simulation using MATLAB R2020a

Time-shifted Pilot-based Scheduling with Adaptive Optimization for Pilot Contamination Reduction in Massive MIMO, Journal of Telecommunications and Information Technology, 2020, nr 4

Massive multiple-input multiple-output (MIMO) is considered to be an emerging technique in wireless communication systems, as it offers the ability to boost channel capacity and spectral efficiency. However, a massive MIMO system requires huge base station (BS) antennas to handle users and suffers from inter-cell interference that leads to pilot contamination. To cope with this, time-shifted pilots are devised for avoiding interference between cells, by rearranging the order of transmitting pilots in different cells. In this paper, an adaptive-elephant-based spider monkey optimization (adaptive ESMO) mechanism is employed for time-shifted optimal pilot scheduling in a massive MIMO system. Here, user grouping is performed with the sparse fuzzy c-means (Sparse FCM) algorithm, grouping users based on such parameters as large-scale fading factor, SINR, and user distance. Here, the user grouping approach prevents inappropriate grouping of users, thus enabling effective grouping, even under the worst conditions in which the channel operates. Finally, optimal time-shifted scheduling of the pilot is performed using the proposed adaptive ESMO concept designed by incorporating adaptive tuning parameters. The efficiency of the adaptive ESMO approach is evaluated and reveals superior performance with the highest achievable uplink rate of 43.084 bps/Hz, the highest SINR of 132.9 dB, and maximum throughput of 2.633 Mbp

Spatial DCT-Based Channel Estimation in Multi-Antenna Multi-Cell Interference Channels

This work addresses channel estimation in multiple antenna multicell interference-limited networks. Channel state information (CSI) acquisition is vital for interference mitigation. Wireless networks often suffer from multicell interference, which can be mitigated by deploying beamforming to spatially direct the transmissions. The accuracy of the estimated CSI plays an important role in designing accurate beamformers that can control the amount of interference created from simultaneous spatial transmissions to mobile users. Therefore, a new technique based on the structure of the spatial covariance matrix and the discrete cosine transform (DCT) is proposed to enhance channel estimation in the presence of interference. Bayesian estimation and Least Squares estimation frameworks are introduced by utilizing the DCT to separate the overlapping spatial paths that create the interference. The spatial domain is thus exploited to mitigate the contamination which is able to discriminate across interfering users. Gains over conventional channel estimation techniques are presented in our simulations which are also valid for a small number of antennas.Comment: Submitted for possible publication. arXiv admin note: text overlap with arXiv:1203.5924 by other author

Performance of Massive MIMO with Interference Decoding

In a massive MIMO system, base stations (BS) utilize a large number of antennas to simultaneously serve several (single or multi-antenna) users at once, where the number of BS antennas is normally assumed to be significantly larger than the number of users. In massive MIMO systems operating in time division duplex (TDD) mode, the channel state information (CSI) is estimated via uplink pilot sequences that are orthogonal in a cell but re-used in other cells. Re-using the pilots, however, contaminates the CSI estimate at BSs by the channel of the users sharing the same pilot in other cells; thus causing pilot contamination which creates coherent interference that, as the number of BS antennas grows, scales at the same rate as the desired signal. Hence, in the asymptotic limits of large antennas, the effects of non-coherent interference terms and noise disappear, except for the pilot contamination interference. A common technique used in the literature to deal with this interference is to treat it as noise (TIN). When using TIN, users' throughput will converge to a constant and thus the benefits of using an ever greater number of BS antennas saturate. However, it is known that the use of TIN in interference networks is only preferred in the weak interference regime, and it is sub-optimal in other regimes (e.g., moderate or strong interference). In this thesis, we show that as the number of BS antennas increases, the pilot contamination interference is no longer weak, and therefore it is beneficial to treat it differently (e.g., decode it jointly with the desired signal) to improve users’ throughput. In the first part of the thesis, we study the performance of interference decoding schemes based on simultaneous unique decoding (SD) and simultaneous non-unique decoding (SND), and show that by doing so the rate saturation effect is eliminated as the number of antennas increases; hence, the per-user rates grow unbounded. We analytically study the performance of two well-known linear combining/precoding methods, namely, MRC/MRT and ZF, for spatially correlated/uncorrelated Rayleigh fading channel models, and obtain closed-form expressions of rate lower bounds for these using a worst-case uncorrelated noise technique for multi-user channels. We compare the performance of the different interference management schemes, TIN/SD/SND, based on the maximum symmetric rate they can offer to the users. Specifically, we first obtain structural results for a symmetric two-cell setting as well as the high SINR regime, that provide insights into the benefits of using interference decoding schemes in different regimes of number of BS antennas. We numerically illustrate the performance of the different schemes and show that with a practical number of antennas, SND strictly outperforms TIN. This gain improves with increasing the number of antennas, and also ZF performs significantly better than MRC/MRT due to better mitigation of multi-user interference. Furthermore, we study the performance of regularized ZF (RZF) via Monte Carlo simulations, and observe that it achieves better rates than ZF for moderately small number of antennas only. Lastly, we numerically investigate the impact of increasing the number of cells, the cell radius, the number of users, the correlation of the channel across antennas and the degree of shadow fading on system performance. In the second part of the thesis, we study the performance of partial interference decoding based on rate splitting (RS) and non-unique decoding. Specifically, we propose to partition each user’s message into two independent layers, and partially decode the pilot contamination interference while treating the remaining part as noise based on a power splitting strategy. In particular, for a two-cell system, we investigate the benefits of an RS scheme based on the celebrated Han-Kobayashi (HK) region, which provides the best known achievable performance for a two-user interference channel (IC). In the case of more than two cells, we propose a generalized RS scheme that non-uniquely decodes each layer of the pilot contamination interference and uses only one power splitting coefficient per IC. In addition, we establish an achievable region for this generalized RS scheme using the non-unique decoding technique. In both cases of two cells and more than two cells and for a practical number of antennas, we numerically study the performance of the proposed RS schemes by numerically optimizing the power splitting coefficients, and show that they achieve significantly higher rates than TIN/SD/SND in all scenarios. Similar to the first part of the thesis, we also numerically examine the impact of increasing the number of cells, the cell radius, the number of users, the correlation of the channel across antennas and the degree of shadow fading on the performance of the RS schemes. Lastly, our simulation results reveal that by replacing the numerically optimized values of the power splitting coefficients with their pre-computed average values (over a large number of realizations), the performance loss is quite negligible, thus reducing the optimization complexity

Spectral Efficiency Maximization of a Massive Multiuser MIMO System via Appropriate Power Allocation

Massive multiuser multiple-input multiple-output (MU-MIMO) systems are being considered for the next generation wireless networks in view of their ability to increase both the spectral and energy efficiencies. For such systems, linear detectors such as zero-forcing (ZF) and maximum-ratio combining (MRC) detectors on the uplink (UL) transmission have been shown to provide near optimal performance. As well, linear precoders such as ZF and maximum-ratio transmission (MRT) precoders on the downlink (DL) transmission offer lower complexity along with a near optimal performance in these systems. One of the most challenging problems in massive MU-MIMO systems is obtaining the channel state information (CSI) at the transmitter as well as the receiver. In such systems, the base station (BS) obtains CSI using pilot sequences, which are transmitted by the users. Due to the channel reciprocity between the UL and DL channels in the time-division duplex (TDD) mode, BS employs CSI obtained to precode the data symbols in DL transmission. To accurately decode the received symbols in the DL transmission, the users also need to acquire CSI. In view of this, a beamforming training (BT) scheme has been proposed in the literature to obtain the estimates of CSI at each user. In this scheme, BS transmits a short pilot sequence to the users in a way such that each user estimates the effective channel gain. Conventionally, the power of the pilot symbols has been considered equal to the power of data symbols for all the users. In this thesis, we pose and answer a basic question about the operation of a base station: How much the spectral efficiency could be improved if the transmit power allocated to the pilot and data symbols of each user are chosen in some optimal fashion? In answering this question and in order to maximize the spectral efficiency for a given total energy budget, some methods of power allocation are proposed. First, we derive a closed-form approximate expression for the achievable downlink rate for the maximum ratio transmission precoder based on small-scale fading in order to evaluate the spectral efficiency in the BT scheme. Then, we propose three methods of power allocation in order to maximize the spectral efficiency for a given total power budget among the users. In the first proposed method, we allocate equal pilot power as well as equal data power for all users in order to maximize the spectral efficiency. In the second proposed method, we allow for the allocation of different data powers among the users, whereas the pilot power for each user is kept the same and is specified. In the third method, we optimally allocate equal pilot power and a different data power for each user in such a way that the spectral efficiency is maximized. Numerical results are obtained showing that all the three proposed methods are superior to the existing methods in terms of spectral efficiency. In addition, they also show that the third proposed method of power allocation outperforms the other two proposed methods in terms of the spectral efficiency. Next, we derive a closed-form approximate expression for the achievable downlink rate for the maximum ratio transmission precoder based on large-scale fading in order to evaluate the spectral efficiency in the BT scheme. Then, we propose four methods of power allocation in order to maximize the spectral efficiency for a given total power budget among the users. In the first method, power is allocated among the pilot and data symbols in such a way that the pilot power as well as the data power for each user is the same. In the second method, power is allocated among the data symbols of the various users, whereas the pilot power for each user is the same and is specified. In this method, the data power for each user is optimally determined to maximize the spectral efficiency. In the third method, power is allocated among the pilot and data symbols of the various users, whereas the pilot power for each user is the same but determined. In this method, the same pilot power along with the various data powers is optimized to maximize the spectral efficiency. Finally, in the fourth method, power is allocated optimally among each of the pilot and data symbols of the various users so as to maximize the spectral efficiency. Numerical results are obtained showing that the performance of the first proposed method is approximately the same as that of the conventional approach. In addition, they also show that the second, third and fourth methods of power allocation yield similar performance in terms of spectral efficiency, and that the spectral efficiency of these methods is much superior to that of the first method or of the conventional method. Finally, we investigate the spectral efficiency of massive MU-MIMO systems on an UL transmission with a very large number of antennas at the base station serving single-antenna users. A practical physical channel model is proposed by dividing the angular domain into a finite number of distinct directions. A lower bound on the achievable rate of the uplink data transmission is derived using a linear detector for each user and employed in defining the spectral efficiency. The lower bound obtained is further modified for the maximum-ratio combining and zero-forcing receivers. A power control scheme based on the large-scale fading is also proposed to maximize the spectral efficiency under the peak power constraint. Experiments are conducted to evaluate the lower bounds obtained and the performance of the proposed method. The numerical results show that the proposed power control method provides a spectral efficiency which is the same as that of the maximum power criterion using the ZF receiver. Further, the proposed method provides a spectral efficiency that is higher than that provided by the maximum power criterion using the MRC receiver