A Decentralized Pilot Assignment Algorithm for Scalable O-RAN Cell-Free Massive MIMO

Radio access networks (RANs) in monolithic architectures have limited adaptability to supporting different network scenarios. Recently, open-RAN (O-RAN) techniques have begun adding enormous flexibility to RAN implementations. O-RAN is a natural architectural fit for cell-free massive multiple-input multiple-output (CFmMIMO) systems, where many geographically-distributed access points (APs) are employed to achieve ubiquitous coverage and enhanced user performance. In this paper, we address the decentralized pilot assignment (PA) problem for scalable O-RAN-based CFmMIMO systems. We propose a low-complexity PA scheme using a multi-agent deep reinforcement learning (MA-DRL) framework in which multiple learning agents perform distributed learning over the O-RAN communication architecture to suppress pilot contamination. Our approach does not require prior channel knowledge but instead relies on real-time interactions made with the environment during the learning procedure. In addition, we design a codebook search (CS) scheme that exploits the decentralization of our O-RAN CFmMIMO architecture, where different codebook sets can be utilized to further improve PA performance without any significant additional complexities. Numerical evaluations verify that our proposed scheme provides substantial computational scalability advantages and improvements in channel estimation performance compared to the state-of-the-art.Comment: This paper has been submitted to IEEE Journal on Selected Areas in Communications for possible publicatio

Resource Allocation for Cell-Free Massive MIMO-aided URLLC Systems Relying on Pilot Sharing

Resource allocation is conceived for cell-free (CF) massive multi-input multi-output (MIMO)-aided ultra-reliable and low latency communication (URLLC) systems. Specifically, to support multiple devices with limited pilot overhead, pilot reuse among the users is considered, where we formulate a joint pilot length and pilot allocation strategy for maximizing the number of devices admitted. Then, the pilot power and transmit power are jointly optimized while simultaneously satisfying the devices’ decoding error probability, latency, and data rate requirements. Firstly, we derive the lower bounds (LBs) of ergodic data rate under finite channel blocklength (FCBL). Then, we propose a novel pilot assignment algorithm for maximizing the number of devices admitted. Based on the pilot allocation pattern advocated, the weighted sum rate (WSR) is maximized by jointly optimizing the pilot power and payload power. To tackle the resultant NP-hard problem, the original optimization problem is first simplified by sophisticated mathematical transformations, and then approximations are found for transforming the original problems into a series of subproblems in geometric programming (GP) forms that can be readily solved. Simulation results demonstrate that the proposed pilot allocation strategy is capable of significantly increasing the number of admitted devices and the proposed power allocation achieves substantial WSR performance gain

Mitigation pilot contamination based on matching technique for uplink cell-free massive MIMO systems

In this paper, the cell-free massive multiple input multiple output (MIMO) network is affected by the pilot contamination phenomenon when a large number of users and a small number of available pilots exists, the quality of service (QoS) will deteriorate due to the low accuracy of the channel estimation because some of users will use the same pilot. Therefore, we address this problem by presenting two novel schemes of pilot assignment and pilot power control design based on the matching technique for the uplink of cell-free massive MIMO systems to maximize spectral efficiency. We first formulate an assignment optimization problem in order to find the best possible pilot sequence to be used by utilizing genetic algorithm (GA) and then propose a Hungarian matching algorithm to solve this formulated problem. Regarding the power control design, we formulate a minimum-weighted assignment problem to assign pilot power control coefficients to the estimated channel’s minimum mean-squared error by considering the access point (AP) selection. Then, we also propose the Hungarian algorithm to solve this problem. Simulation results show that our proposed schemes outperform the state-of-the-art techniques concerning both the pilot assignment and the pilot power control design by achieving a 15% improvement in the spectral efficiency. Finally, the computational complexity analysis is provided for the proposed schemes compared with the state-of-the-art techniques

Uplink Performance of Hardware-Impaired Cell-Free Massive MIMO with Multi-Antenna Users and Superimposed Pilots

Cell-free massive multiple-input multiple-output (mMIMO) has recently been proposed to improve cell edge performance. However, most prior works consider perfect hardware impairments (HIs), which are difficult to be achieved in practical systems. This paper studies the impact of HI in an uplink cell-free mMIMO system with both multi-antenna access points (APs) and multi-antenna user terminals (UTs) under the Weichselberger channel model.Firstly, we study a two-layer decoding scheme with local minimum mean-squared error or maximum ratio combining at the AP side and with optimal large-scale fading decoding in the central processing unit. We derive novel closed-form SE expressions and prove that the effect of HI can be mitigated in the case of UTs with multiple antennas. However, the achievable SE is constrained by the pilot contamination and pilot overhead. To this end, the superimposed pilot (SP) transmission method is considered in this paper, where all the coherence intervals are used for both pilot and data symbols transmission. Finally, numerical results verify our derived expressions and reveal the relationship between HI and the number of antennas per UT for different pilot schemes. Note that the advantages of SP over regular pilots disappear when the hardware quality decreases with multi-antenna UTs

Towards low complexity matching theory for uplink wireless communication systems

Millimetre wave (mm-Wave) technology is considered a promising direction to achieve the high quality of services (QoSs) because it can provide high bandwidth, achieving a higher transmission rate due to its immunity to interference. However, there are several limitations to utilizing mm-Wave technology, such as more extraordinary precision hardware is manufactured at a higher cost because the size of its components is small. Consequently, mm-Wave technology is rarely applicable for long-distance applications due to its narrow beams width. Therefore, using cell-free massive multiple input multiple output (MIMO) with mm-Wave technology can solve these issues because this architecture of massive MIMO has better system performance, in terms of high achievable rate, high coverage, and handover-free, than conventional architectures, such as massive MIMO systems’ co-located and distributed (small cells). This technology necessitates a significant amount of power because each distributed access point (AP) has several antennas. Each AP has a few radio frequency (RF) chains in hybrid beamforming. Therefore more APs mean a large number of total RF chains in the cell-free network, which increases power consumption. To solve this problem, deactivating some antennas or RF chains at each AP can be utilized. However, the size of the cell-free network yields these two options as computationally demanding. On the other hand, a large number of users in the cell-free network causes pilot contamination issue due to the small length of the uplink training phase. This issue has been solved in the literature based on two options: pilot assignment and pilot power control. Still, these two solutions are complex due to the cell-free network size. Motivated by what was mentioned previously, this thesis proposes a novel technique with low computational complexity based on matching theory for antenna selection, RF chains activation, pilot assignment and pilot power control. The first part of this thesis provides an overview of matching theory and the conventional massive MIMO systems. Then, an overview of the cell-free massive MIMO systems and the related works of the signal processing techniques of the cell-free mm-Wave massive MIMO systems to maximize energy efficiency (EE), are provided. Based on the limitations of these techniques, the second part of this thesis presents a hybrid beamforming architecture with constant phase shifters (CPSs) for the distributed uplink cell-free mm-Wave massive MIMO systems based on exploiting antenna selection to reduce power consumption. The proposed scheme uses a matching technique to obtain the number of selected antennas which can contribute more to the desired signal power than the interference power for each RF chain at each AP. Therefore, the third part of this thesis solves the issue of the huge complexity of activating RF chains by presenting a low-complexity matching approach to activate a set of RF chains based on the Hungarian method to maximize the total EE in the centralized uplink of the cell-free mm-Wave massive MIMO systems when it is proposed hybrid beamforming with fully connected phase shifters network. The pilot contamination issue has been discussed in the last part of this thesis by utilizing matching theory in pilot assignment and pilot power control design for the uplink of cell-free massive MIMO systems to maximize SE. Firstly, an assignment optimization problem has been formulated to find the best possible pilot sequences to be inserted into a genetic algorithm (GA). Therefore, the GA will find the optimal solution. After that, a minimum-weighted assignment problem has been formulated regarding the power control design to assign pilot power control coefficients to the quality of the estimated channel. Then, the Hungarian method is utilized to solve this problem. The simulation results of the proposed matching theory for the mentioned issues reveal that the proposed matching approach is more energy-efficient and has lower computational complexity than state-of-the-art schemes for antenna selection and RF chain activation. In addition, the proposed matching schemes outperform the state-of-the-art techniques concerning the pilot assignment and the pilot power control design. This means that network scalability can be guaranteed with low computational complexity

Analysis and Design of Cell-Free Massive MIMO Systems under Spatially Correlated Fading Channels

Mención Internacional en el título de doctorWireless communications have become a key pillar in our modern society. It can be hard to think of a service that somehow does not rely on them. Particularly, mobile networks are one of the most necessary technologies in our daily life. This produces that the demand for data rates is by no means stopping from increasing. The cellular architecture is facing a crucial challenge under limited performance by interference and spectrum saturation. This involves cell-edge users experiencing poor performance due to the close vicinity of base stations (BSs) using the same carrier frequency. Based on a combination of the coordinated multi-point (CoMP) technique and traditional massive multiple-input multiple-output (MIMO) systems, cell-free (CF) massive MIMO networks have irrupted as a solution for avoiding inter-cell interference issues and for providing uniform service in large coverage areas. This thesis focuses on the analysis and design of CF massive MIMO networks assuming a spatially correlated fading model. A general-purpose channel model is provided and the whole network functioning is given in detail. Despite the many characteristics a CF massive MIMO system shares with conventional colocated massive MIMO its distributed nature brings along new issues that need to be carefully accounted for. In particular, the so-called channel hardening effect that postulates that the variance of the compound wireless channel experienced by a given user from a large number of transmit antennas tends to vanish, effectively making the channel deterministic. This critical assumption, which permeates most theoretical results of massive MIMO, has been well investigated and validated in centralized architectures, however, it has received little attention in the context of CF massive MIMO networks. Hardening in CF architectures is potentially compromised by the different large-scale gains each access point (AP) impinges on the transmitted signal to each user, a condition that is further stressed when not all APs transmit to all users as proposed in the user-centric (UC) variations of CF massive MIMO. In this document, the presence of channel hardening in this new architecture scheme is addressed using distributed and cooperative precoders and combiners and different power control strategies. It is shown that the line-of-sight (LOS) component, spatially correlated antennas, and clustering schemes have an impact on how the channel hardens. In addition, we examine the existent gap between the estimated achievable rate and the true network performance when channel hardening is compromised. Exact closed-form expressions for both a hardening metric and achievable downlink (DL) and uplink (UL) rates are given as well. We also look into the pilot contamination problem in the UL and DL with different degrees of cooperation between the APs. The optimum minimum mean-squared error (MMSE) processing can take advantage of large-scale fading coefficients for canceling the interference of pilot-sharing users and thus achieves asymptotically unbounded capacity. However, it is computationally demanding and can only be implemented in a fully centralized network. Here, sub-optimal schemes are derived that provide unbounded capacity with much lower complexity and using only local channel estimates but global channel statistics. This makes them suited for both centralized and distributed networks. In this latter case, the best performance is achieved with a generalized maximum ratio combiner that maximizes a capacity bound based on channel statistics only.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Rui Dinis.- Secretario: María Julia Fernández-Getino García.- Vocal: Carmen Botella Mascarel

Half-Duplex APs with Dynamic TDD vs. Full-Duplex APs in Cell-Free Systems

In this paper, we present a comparative study of half-duplex (HD) access points (APs) with dynamic time-division duplex (DTDD) and full-duplex (FD) APs in cell-free (CF) systems. Although both DTDD and FD CF systems support concurrent downlink transmission and uplink reception capability, the sum spectral efficiency (SE) is limited by various cross-link interferences. We first present a novel pilot allocation scheme that minimizes the pilot length required to ensure no pilot contamination among the user equipments (UEs) served by at least one common AP. Then, we derive the sum SE in closed form, considering zero-forcing combining and precoding along with the signal-to-interference plus noise ratio optimal weighting at the central processing unit. We also present a provably convergent algorithm for joint uplink-downlink power allocation and uplink/downlink mode scheduling of the APs (for DTDD) to maximize the sum SE. Our numerical results illustrate the superiority of the proposed algorithms over several benchmarks and show that the sum SE with DTDD can outperform an FD CF system with similar antenna density. Thus, DTDD combined with CF is a promising alternative to FD that attains the same performance using HD APs, while obviating the burden of intra-AP interference cancellation.Comment: 17 pages, 9 Figure