C-RAN CoMP Methods for MPR Receivers

The growth in mobile network traffic due to the increase in MTC (Machine Type Communication) applications, brings along a series of new challenges in traffic routing and management. The goals are to have effective resolution times (less delay), low energy consuption (given that wide sensor networks which are included in the MTC category, are built to last years with respect to their battery consuption) and extremely reliable communication (low Packet Error Rates), following the fifth generation (5G) mobile network demands. In order to deal with this type of dense traffic, several uplink strategies can be devised, where diversity variables like space (several Base Stations deployed), time (number of retransmissions of a given packet per user) and power spreading (power value diversity at the receiver, introducing the concept of SIC and Power-NOMA) have to be handled carefully to fulfill the requirements demanded in Ultra-Reliable Low-Latency Communication (URLLC). This thesis, besides being restricted in terms of transmission power and processing of a User Equipment (UE), works on top of an Iterative Block Decision Feedback Equalization Reciever that allows Multi Packet Reception to deal with the diversity types mentioned earlier. The results of this thesis explore the possibility of fragmenting the processing capabilities in an integrated cloud network (C-RAN) environment through an SINR estimation at the receiver to better understand how and where we can break and distribute our processing needs in order to handle near Base Station users and cell-edge users, the latters being the hardest to deal with in dense networks like the ones deployed in a MTC environment

LSTM-Aided Hybrid Random Access Scheme for 6G Machine Type Communication Networks

In this paper, an LSTM-aided hybrid random access scheme (LSTMH-RA) is proposed to support diverse quality of service (QoS) requirements in 6G machine-type communication (MTC) networks, where massive MTC (mMTC) devices and ultra-reliable low latency communications (URLLC) devices coexist. In the proposed LSTMH-RA scheme, mMTC devices access the network via a timing advance (TA)-aided four-step procedure to meet massive access requirement, while the access procedure of the URLLC devices is completed in two steps coupled with the mMTC devices' access procedure to reduce latency. Furthermore, we propose an attention-based LSTM prediction model to predict the number of active URLLC devices, thereby determining the parameters of the multi-user detection algorithm to guarantee the latency and reliability access requirements of URLLC devices.We analyze the successful access probability of the LSTMH-RA scheme. Numerical results show that, compared with the benchmark schemes, the proposed LSTMH-RA scheme can significantly improve the successful access probability, and thus satisfy the diverse QoS requirements of URLLC and mMTC devices

Sub-graph based joint sparse graph for sparse code multiple access systems

Sparse code multiple access (SCMA) is a promising air interface candidate technique for next generation mobile networks, especially for massive machine type communications (mMTC). In this paper, we design a LDPC coded SCMA detector by combining the sparse graphs of LDPC and SCMA into one joint sparse graph (JSG). In our proposed scheme, SCMA sparse graph (SSG) defined by small size indicator matrix is utilized to construct the JSG, which is termed as sub-graph based joint sparse graph of SCMA (SG-JSG-SCMA). In this paper, we first study the binary-LDPC (B-LDPC) coded SGJSG- SCMA system. To combine the SCMA variable node (SVN) and LDPC variable node (LVN) into one joint variable node (JVN), a non-binary LDPC (NB-LDPC) coded SG-JSG-SCMA is also proposed. Furthermore, to reduce the complexity of NBLDPC coded SG-JSG-SCMA, a joint trellis representation (JTR) is introduced to represent the search space of NB-LDPC coded SG-JSG-SCMA. Based on JTR, a low complexity joint trellis based detection and decoding (JTDD) algorithm is proposed to reduce the computational complexity of NB-LDPC coded SGJSG- SCMA system. According to the simulation results, SG-JSGSCMA brings significant performance improvement compare to the conventional receiver using the disjoint approach, and it can also outperform a Turbo-structured receiver with comparable complexity. Moreover, the joint approach also has advantages in terms of processing latency compare to the Turbo approaches

Rate-Splitting Random Access Mechanism for Massive Machine Type Communications in 5G Cellular Internet-of-Things

The cellular Internet-of-Things has resulted in the deployment of millions of machine type communication (MTC) devices under the coverage of a single gNodeB (gNB). These massive number of devices should connect to the gNodeB (gNB) via the random access channel (RACH) mechanism. Moreover, the existing RACH mechanisms are inefficient when dealing with such large number of devices. To address this issue, we propose the rate-splitting random access (RSRA) mechanism, which uses rate splitting and decoding in rate-splitting multiple access (RSMA), to improve the RACH success rate. The proposed mechanism divides the message into common and private messages and enhances the decoding performance. We demonstrate, using extensive simulations, that the proposed RSRA mechanism significantly improves the success rate of MTC in cellular IoT networks. We also evaluate the performance of the proposed mechanism with increasing number of devices and received power difference. © 2021 IEEE

Protocol for Extreme Low Latency M2M Communication Networks

As technology evolves, more Machine to Machine (M2M) deployments and mission critical services are expected to grow massively, generating new and diverse forms of data traffic, posing unprecedented challenges in requirements such as delay, reliability, energy consumption and scalability. This new paradigm vindicates a new set of stringent requirements that the current mobile networks do not support. A new generation of mobile networks is needed to attend to this innovative services and requirements - the The fifth generation of mobile networks (5G) networks. Specifically, achieving ultra-reliable low latency communication for machine to machine networks represents a major challenge, that requires a new approach to the design of the Physical (PHY) and Medium Access Control (MAC) layer to provide these novel services and handle the new heterogeneous environment in 5G. The current LTE Advanced (LTE-A) radio access network orthogonality and synchronization requirements are obstacles for this new 5G architecture, since devices in M2M generate bursty and sporadic traffic, and therefore should not be obliged to follow the synchronization of the LTE-A PHY layer. A non-orthogonal access scheme is required, that enables asynchronous access and that does not degrade the spectrum. This dissertation addresses the requirements of URLLC M2M traffic at the MAC layer. It proposes an extension of the M2M H-NDMA protocol for a multi base station scenario and a power control scheme to adapt the protocol to the requirements of URLLC. The system and power control schemes performance and the introduction of more base stations are analyzed in a system level simulator developed in MATLAB, which implements the MAC protocol and applies the power control algorithm. Results showed that with the increase in the number of base stations, delay can be significantly reduced and the protocol supports more devices without compromising delay or reliability bounds for Ultra-Reliable and Low Latency Communication (URLLC), while also increasing the throughput. The extension of the protocol will enable the study of different power control algorithms for more complex scenarios and access schemes that combine asynchronous and synchronous access

Resource allocation for NOMA wireless systems

Power-domain non-orthogonal multiple access (NOMA) has been widely recognized as a promising candidate for the next generation of wireless communication systems. By applying superposition coding at the transmitter and successive interference cancellation at the receiver, NOMA allows multiple users to access the same time-frequency resource in power domain. This way, NOMA not only increases the system’s spectral and energy efficiencies, but also supports more users when compared with the conventional orthogonal multiple access (OMA). Meanwhile, improved user fairness can be achieved by NOMA. Nonetheless, the promised advantages of NOMA cannot be realized without proper resource allocation. The main resources in wireless communication systems include time, frequency, space, code and power. In NOMA systems, multiple users are accommodated in each time/frequency/code resource block (RB), forming a NOMA cluster. As a result, how to group the users into NOMA clusters and allocate the power is of significance. A large number of studies have been carried out for developing efficient power allocation (PA) algorithms in single-input single-output (SISO) scenarios with fixed user clustering. To fully reap the gain of NOMA, the design of joint PA and user clustering is required. Moreover, the study of PA under multiple-input multiple-output (MIMO) systems still remains at an incipient stage. In this dissertation, we develop novel algorithms to allocate resource for both SISO-NOMA and MIMO-NOMA systems. More specifically, Chapter 2 compares the system capacity of MIMO-NOMA with MIMO-OMA. It is proved analytically that MIMO-NOMA outperforms MIMO-OMA in terms of both sum channel capacity and ergodic sum capacity when there are multiple users in a cluster. Furthermore, it is demonstrated that the more users are admitted to a cluster, the lower is the achieved sum rate, which illustrates the tradeoff between the sum rate and maximum number of admitted users. Chapter 3 addresses the PA problem for a general multi-cluster multi-user MIMONOMA system to maximize the system energy efficiency (EE). First, a closed-form solution is derived for the corresponding sum rate (SE) maximization problem. Then, the EE maximization problem is solved by applying non-convex fractional programming. Chapter 4 investigates the energy-efficient joint user-RB association and PA problem for an uplink hybrid NOMA-OMA system. The considered problem requires to jointly optimize the user clustering, channel assignment and power allocation. To address this hard problem, a many-to-one bipartite graph is first constructed considering the users and RBs as the two sets of nodes. Based on swap matching, a joint user-RB association and power allocation scheme is proposed, which converges within a limited number of iterations. Moreover, for the power allocation under a given user-RB association, a low complexity optimal PA algorithm is proposed. Furthermore, Chapter 5 focuses on securing the confidential information of massive MIMO-NOMA networks by exploiting artificial noise (AN). An uplink training scheme is first proposed, and on this basis, the base station precodes the confidential information and injects the AN. Following this, the ergodic secrecy rate is derived for downlink transmission. Additionally, PA algorithms are proposed to maximize the SE and EE of the system. Finally, conclusions are drawn and possible extensions to resource allocation in NOMA systems are discussed in Chapter 6