The study of self organized networks is considered a key element in developing the new generation of cellular networks. Mobile service providers are adopting new technologies such as small cells and precoding to deploy their networks according to 5G standards. As these type of technologies gain more importance and popularity, network self organization become a more essential function in operating the network resources. Self organized networks have been classified into three main categorizes: self optimization, self configuration, and self healing. The first two categories showed further development and research interest when compared to self-healing. Due to the high density nature of small cells, using massive antennas in the network, and their susceptibility to failures for various reasons, the demand for a clear self-healing process and architecture is deemed urgent. In this paper the current self-healing process in addition to the fault tolerance aspects for the future 5G are studied and a new process model for organizing the self-healing process is proposed. The new process model is meant to map the different functionalities needed to perform a successful self healing process. The model with the proposed descriptive network architecture aims to identify the different functions within the self-healing process model. In order to test the operation ability of the model, a new big data aspect is added to the network architecture to aid in analyzing the huge amount of data needed to efficiently perform the self-healing process. Results show that the proposed precoding technique in conjunction with the machine learning algorithm based on a decision tree model that uses empirical data collected from the network can identify the status of cells (healthy, congested or failing) and suitable self-healing procedures can be triggered to recover the cell accordingly.

In this paper, we propose a new, robust near-optimal mutual information combined zero-forcing per-group precoding (ZF-PGP) method for finite alphabets with imperfect channel state information (CSI) at the receiver. ZF-PGP achieves very high gains over ZF precoding techniques, while it simultaneously offers individually separate streams to reach individual user equipment (UE), i.e., it obliterates the need for coordinated, joint decoding by the group's UEs. The proposed robust ZF-PGP scheme comprises an inner linear beamformer (BF), which relies on second-order CSI and is based on the massive MIMO-based joint division and multiplexing for finite alphabets (JSDM-FA) to form orthogonal user groups, and an outer linear precoder that relies on instantaneous group CSI to form a per-group precoding within groups (PGP-WG) with separate data streams to each user. As we show by multiple examples, for a uniform linear array (ULA), the proposed ZF-PGP technique is very efficient, near-optimal design with reduced complexity at the UEs. Due to JSDM-FA second-order CSI inner beamforming, the groups are easily identified. We also demonstrate the robustness of the proposed precoding techniques to channel estimation errors, showing minimal performance loss.

In this paper, the problem of designing a forward link linear precoder for Massive Multiple-Input Multiple-Output (MIMO) systems in conjunction with Quadrature Amplitude Modulation (QAM) is addressed. A challenge in such system design is to consider finite alphabet inputs, especially with larger constellation sizes such as M ≥ 16. First, we employ a novel and efficient methodology that allows for a sparse representation of multiple users and groups in a fashion similar to Joint Spatial Division and Multiplexing (JSDM), thus offering an extension of JSDM to finite alphabet data symbols. We term the new approach JSDM for finite alphabets (JSDM-FA). We show that similarly to ordinary JSDM, the optimal pre-beamforming matrix for Massive MIMO in JSDM-FA becomes the DFT matrix. The proposed methodology is next applied jointly with the complexity-reducing Per-Group Processing within groups (PGP-WG) technique, on a per user group basis, in conjunction with QAM modulation and in simulations, for constellation size up to M = 64. We show by numerical results that the precoders developed offer significantly better performance than the configuration with no precoder or the plain beamformer and with M ≥ 16.16.

In this paper, the problem of designing a linear precoder for Multiple-Input Multiple-Output (MIMO) systems in conjunction with Quadrature Amplitude Modulation (QAM) is addressed. First, a novel and efficient methodology to evaluate the input-output mutual information for a general Multiple-Input Multiple-Output (MIMO) system as well as its corresponding gradients is presented, based on the Gauss-Hermite quadrature rule. Then, the method is exploited in a block coordinate gradient ascent optimization process to determine the globally optimal linear precoder with respect to the MIMO input-output mutual information for QAM systems with relatively moderate MIMO channel sizes. The proposed methodology is next applied in conjunction with the complexity-reducing per-group processing (PGP) technique to both perfect channel state information at the transmitter (CSIT) as well as statistical channel state information (SCSI) scenarios, with large transmitting and receiving antenna size, and for constellation size up to M = 64. We show by numerical results that the precoders developed offer significantly better performance than the configuration with no precoder as well as the maximum diversity precoder for QAM with constellation sizes M = 16; 32, and 64 and for MIMO channel size up to 100 ⌉x 100.

In this paper, the problem of designing a linear precoder for multiple-input multiple-output (MIMO) systems in conjunction with quadrature amplitude modulation (QAM) is addressed. First, a novel and efficient methodology to evaluate the input-output mutual information for a general MIMO system as well as its corresponding gradients is presented, based on the Gauss-Hermite quadrature rule. Then, the method is exploited in a block coordinate gradient ascent optimization process to determine the globally optimal linear precoder with respect to the MIMO input-output mutual information for QAM systems with relatively moderate MIMO channel sizes. The proposed methodology is next applied in conjunction with the complexity-reducing per-group processing technique to both perfect channel state information (CSI) at the transmitter as well as statistical CSI (Statistical CSI) scenarios, with large transmitting and receiving antenna sizes, and for constellation size up to M = 64. We show by the numerical results that the precoders developed offer significantly better performance than the configuration with no precoder as well as the maximum diversity precoder for QAM with constellation sizes M = 16, 32, and 64 and for MIMO channel size up to 100 × 100.

In this paper, the problem of designing a linear precoder for Multiple-Input Multiple-Output (MIMO) systems employing Low-Density Parity-Check (LDPC) codes is addressed under the constraint of minimizing the dependence between the system's receiving branches, thus reducing the relevant transmitter and receiver complexities. Our approach constitutes an interesting generalization of Bit-Interleaved Coded Modulation with Multiple Beamforming (BICMB) which has shown many benefits in MIMO systems. We start with a Pareto optimal surface modeling of the system and show the difficulty involved in the corresponding optimization problem. We then propose an alternative, practical technique, called Per-Group Precoding (PGP), which groups together multiple input symbol streams and corresponding receiving branches in the “virtual” channel domain (after singular value decomposition of the original MIMO channel), and thus results in independent transmitting/receiving streams between groups. We show with numerical results that PGP offers almost optimal performance, albeit with significant reduction both in the precoder optimization and LDPC EXIT chart based decoding complexities.

An optimized iterative (Turbo) receiver for Orthogonal Frequency Division Multiplexing (OFDM) transmission is proposed for improved performance when used with type-I hybrid Automatic Repeat Request (ARQ) protocols. The proposed receiver is a Maximum Aposteriori Expectation-Maximization (MAP-EM) Turbo processor that exploits information from all available transmissions of a packet, including failed and new ones. Two distinct practical problems associated with OFDM are considered: (i) Clipping due to non-linearities in the transmit amplifier, and (ii) Carrier frequency offset (CFO). In the optimized scheme, failed transmissions are combined with the new ones to form an iterative receiver that jointly estimates the channel, compensates for the distortion (clipping, or CFO) and decodes the message. The modulation employed is M-ary Phase Shift Keying (MPSK). The system uses an embedded pilot structure for initial channel estimation of the channel, which is assumed doubly-selective. It is shown that gains on the order of 3 dB are achieved in the packet rejection probability with the proposed system. The performance of the optimized system is close to that of the ideal system, i.e. one that performs packet combining with perfect channel knowledge, no clipping, and no CFO.

In this paper, we propose an optimized ARQ iterative receiver for OFDM transmission, suitable for application in rapidly varying multipath channels. The receiver is an optimized MAP Turbo processor that exploits information from all available transmissions in an optimized way, using only the minimum required number of pilots for initial channel estimation. Our model does not account for CFO or transmitter non-linearities. The system uses an imbedded pilot structure in the frequency domain to initially estimate the channel. Further improvement of these estimates takes place based on the EM algorithm and the available received vectors, including all antennas and transmissions of the OFDM word. We show that this configuration achieves high gains compared to a standard ARQ system with packet combining and soft decision decoding of a higher constraint length, nu = 7 convolutional code. Finally, the potential of the approach in more realistic models (e.g. with CFO or nonlinear transmission) is established due to the minimum number of pilots employed herein.

The paper presents a possible integrated system concept for a direct sequence spread spectrum CDMA radio access system suitable for third-generation mobile radio. The system has been conceived to take account of such diverse services as low bit rate voice and quasi-broadband services at rates of up to 256 kb/s. Broadband services imply the use of the ATM transmission technique, and particular attention is paid to the mutual impact of CDMA and ATM. An efficient automatic repeat request technique is described which gives a suitably low overall error rate and a soft capacity limit. The proposed solution represents a quantum advance on today's CDMA solutions and integrates well with the ATM fixed network.>

Exact expressions for the probabilities P(l,m-l/k) of l correct packet receptions and m-l erroneous ones, out of total k packets contending in a slot, are presented for the case of frequency-hopped spread-spectrum random-access slotted networks employing random frequency hopping patterns. These expressions are difficult to evaluate numerically for values of m>3. However, their numerical analysis indicates that under light traffic conditions these probability values are very close to the ones provided by the independent receiver operation assumption, under which the distribution of multireception obeys the binomial law.>