The development of 6G wireless technologies is rapidly advancing, with the 3rd Generation Partnership Project (3GPP) entering the pre-standardization phase and aiming to deliver the first specifications by 2028. This paper explores the OpenAirInterface (OAI) project, an open-source initiative that plays a crucial role in the evolution of 5G and future 6G networks. OAI provides a comprehensive implementation of 3GPP and O-RAN compliant networks, including Radio Access Network (RAN), Core Network (CN), and software-defined User Equipment (UE) components. This paper details the history and evolution of OAI, its licensing model, and the various projects under its umbrella, such as RAN, the CN, and the Operations, Administration and Maintenance (OAM) projects. It also highlights the development methodology, Continuous Integration/Continuous Delivery (CI/CD) processes, and end-to-end systems powered by OAI. Furthermore, the paper discusses the potential of OAI for 6G research, focusing on spectrum, reflective intelligent surfaces, and Artificial Intelligence (AI)/Machine Learning (ML) integration. The open-source approach of OAI is emphasized as essential for tackling the challenges of 6G, fostering community collaboration, and driving innovation in next-generation wireless technologies.

Virtualization technology is considered an effective measure to enhance resource utilization and interference management via radio resource abstraction in heterogeneous networks (HetNet). The critical challenge in wireless virtualization is virtual resource allocation on which substantial works have been done. However, most existing researches on virtual resource allocation focus on improving total utility. Different from the existing works, we investigate the dynamic‐aware virtual radio resource allocation in virtualization based HetNet considering utility and fairness. A virtual radio resource management framework is proposed, where the radio resources of different physical networks are virtualized into a virtual resource pool and mobile virtual network operators (MVNOs) compete for virtual resources from the pool to provide service to users. A virtual radio resource allocation algorithm based on biological model is developed, considering system utility, fairness, and dynamics. Simulation results are provided to verify that the proposed virtual resource allocation algorithm not only converges within a few iterations, but also achieves a better trade‐off between total utility and fairness than existing algorithm. Besides, it can also be utilized to analyze the population dynamics of system.

Cognitive radio (CR) aims at enabling the coexistence between legacy systems called primary users (PU) and secondary users (SU), provided the SU do not (significantly) cause interference on PU links. Massive MIMO systems on the other hand yield significant performance and reliability enhancement. In this paper, we investigate the capacity of both PU and SU systems using multi-user (MU) massive MIMO and time division duplex (TDD). TDD indeed permits to estimate the channel state information (CSI) at the PU/SU transmitters to perform linear precoding, taking advantage of the channel reciprocity. The capacity is derived considering the CSI imperfections, the non-reciprocal radio frequency front-ends as well as antenna coupling effects. These impairments can be compensated using reciprocity calibration techniques we recently developed. Extending these techniques to MU massive MIMO, we evaluate interference cancellation precoders. Simulations reveal performance improvements using the massive MIMO reciprocity-based precoder in a CR approach.

In this paper we address the problem of Weighted Sum Rate (WSR) maximization for a K-user Multiple-Input Single-Output (MISO) cognitive Interference Channel (IFC) with linear transmit beamforming (BF) vectors in an underlay cognitive radio setting. We consider a set of L single-antenna Primary receivers to which the cognitive system can causes a limited amount of interference. We thus propose an iterative algorithm to determine the BF vectors for the secondary transmission. The optimization of the Lagrange multipliers involved in the optimization problem is based on the subgradient method. The expression of the BF vector can be interpreted as dual Uplink (UL) MMSE receiver that takes into account the interference caused by a fictitious link between the primary user and secondary base station. Finally Deterministic Annealing is applied to make the convergence of the algorithm easier.

In this paper a K user multi-input single-output (MISO) interference channel (IFC) is considered where the interference at each receiver is treated as an additional Gaussian noise contribution (Noisy IFC). We address the MISO downlink (DL) beamformer design and power allocation for maximizing the minimum SINR with per base station power constraints and imposing a minimum quality of service (QoS) requirement for each receiver. We study a distributed iterative algorithm for solving the given beamforming problem based on a combination of duality principles and the property that maxmin SINR problem is strictly related to the total power minimization problem. Finally we show that it is possible to characterize the entire Pareto boundary of the SINR (Rate) region for a K-user MISO IFC solving a sequence of maxmin SINR imposing different set of QoS constraints.

We study a practical version of the broadcast channel (BC) where the channel state information at the transmitter (CSIT) is available only for some of the users, dubbing the system as mixed CSIT. We start with the simplest instance of such a heterogeneous BC where a multi-antenna transmitter base-station (BS) is trying to communicate data to two single-antenna user equipments (UE), having the perfect CSIT about UE1 and no CSIT about UE2. We propose a very simple transmission strategy at the BS for such a system and compare its performance with the interference alignment solution proposed elsewhere which achieves full degrees-of-freedom (DOF) when channel coherence lengths and switching instants abide by certain restrictions. Then with an additional receive antenna granted to UE2 (whose CSIT is not available) and keeping the same CSIT perspective, achievable rates for two users are derived and compared with earlier schemes. Analytical and simulation results show that this additional receive antenna brings significant gains in the system with the same transmission strategy and without any extra requirement of channel training or feedback.

A base station (BS) transmits (Tx) and receives (Rx) signals to and from multiple mobile users (MU) through a two-way amplify and forward (AF) relay station (RS) using a two-phase protocol. The BS and the RS are both equipped with multiple antennas. In the first phase (time or frequency), the BS and all MU transmit their signals to the RS. In the second phase, the relay transmits towards the BS and MU a transformed signal in a broadcast (BC) fashion. We present a Weighted Sum Rate (WSR) maximizing approach. The optimization problem is similar as e.g., the multi-input multi-output (MIMO) BC where instead of alternating between Tx and Rx filters, one now alternates between Tx filters at BS and RS. Furthermore, we show that in the two-phase relaying considered here, there is not only a rate region for the MU in the downlink, but the coupled optimization of the BS transmitter and the RS receiver/transmitter leads in fact to an uplink/downlink rate region. Different UL and DL rates in this region can be achieved through rate tradeoffs across individual users.

Centralized algorithms for weighted sum rate (WSR) maximization for the K-user frequency-flat MIMO Interference Channel (MIMO IFC) with full channel state information (CSI) are considered. Maximization of WSR is desirable since it allows the system to cover all the rate tuples on the rate region boundary for a given MIMO IFC. First, we propose an iterative algorithm to design optimal linear transmitters and receivers. The transmitters and receivers are optimized to maximize the WSR of the MIMO IFC. Subsequently, we propose a greedy user selection algorithm based on the maximum WSR algorithm that can be applied to select a subset of transmit-receive pairs that cooperate in the interest of maximizing the sum-rate of the resulting cooperative network. To the best of our knowledge this is the first time user selection has been proposed in the context of the MIMO IFC.

Closed loop transmit diversity has already been adopted by 3GPP for MIMO HSDPA in the form of TxAA and its dual stream counterpart, D-TxAA. While both these transmission techniques provide performance gains for single user (SU) scenarios, they both introduce multi-user interference in the downlink in multi-user (MU) scenarios. In this paper, we study the extension of these transmission techniques to the multiuser case which entail minimal changes to the existing standard. To this end, we consider the classical MMSE chip equalizer receivers that feed back beamforming weights so as to maximize the receive SINR at each user equipment (UE). Given that the base station (BS) has to use these weights to transmit data to the UEs, we compare practical and realistic strategies that BS can employ in order to maximize downlink capacity. We derive the SINR expression for MMSE chip equalizer receivers for the general case of MU-TxAA which is used at the receivers to select optimum feedback weights. We investigate different multiuser schemes for HSDPA in the downlink (DL), compare their performance and suggest optimal strategies for single and dual stream transmission for both single and multi-antenna receivers and corroborate our arguments with simulation results. We show that for the case of single antenna receivers, scheduling users with same beamforming weights maximizes downlink capacity in TxAA. For the D-TxAA with multiple antennas at receivers (MIMO) we show that SDMA outperforms spatial multiplexing in terms of maximizing DL capacity.

We address the issue of low complexity linear equalization for cyclic-prefix (CP) and zero-padded (ZP) block transmissions (OFDM). While cyclic-prefix (CP) OFDM does not exploit frequency diversity offered by multipath fading, use of appropriate redundant linear preceding permits a linear equalizer (LE) to benefit from full diversity in the frequency selective channel. We exploit excess time of block transmission (TX) for low-complexity (and full-diversity) linear equalization. Relying on specific structure in the TX scheme, it is shown that excess time can take different forms and impacts diversity order of linear (block) equalization at the receiver (RX). We focus on frequency selective channels and revisit full-diversity low- complexity LE for the ZP case. We discuss special cases of ZP-OFDM with excess time that admit full-diversity LE and draw parallels with the standard ZP case.

We revisit CDMA downlink receivers (RX) based on linear minimum mean-square error (LMMSE) chip-equalizer front-end followed by a Walsh code correlator for single-input-single (multi)- output (SISO or SIMO) channels with the purpose of highlighting the non-trivial question of bias in the output of the equalizer. In a linear time-invariant channel, this bias is constant at chip-equalizer output, but evolves over time at code correlator output impacting Signal-to-Interference-plus-noise ratio (SINR) and thus achievable rates in such receivers. In principle, this bias must be taken into account in further RX/decoding stages even if its impact is small. It is shown that a new class of maximum-likelihood (ML) RX leading to potential performance gains is obtained when properly accounting for symbol-level bias across a set of user codes. These results are extended to the multi-input-multi-output (MIMO) case of UMTS high-speed downlink packet access (HSDPA).

Optimal linear receivers for MIMO HSDPA (as for SISO/SIMO) are symbol-level (deterministic) multiuser receivers, known unfortunately to be time-varying in nature and thus prohibitively complex. Traditional less complex alternative is dimensionality-reducing linear chip-equalization followed by further non-linear (interference canceling) or joint detection stages to improve symbol estimates. Well-known versions of former include inter-stream Successive Interference Canceling (SIC) involving all codes while the latter leads to per-code joint spatial maximum-likelihood (ML) receiver. We investigate the class of MIMO HSDPA receivers based upon LMMSE chip- level MIMO (equalizer) front end, and introduce two (one static and the other time-varying) models of the resulting spatial channel, a consequence of treating the scrambler as random or deterministic. It is shown that in the random case, statistical properties can be exploited to design MIMO receivers while the deterministic point-of-view leads to another set of reduced- dimensionality linear receivers or interference cancelers.

We consider SINR maximizing receivers based on the concept of chip-level filtering and symbol level equalization for WCDMA downlink. In this contribution we propose a new class of receivers based on channel sparsifying linear pre-processing at chip-rate followed by time-varying symbol level equalizers. Due to a sparse structure imposed on the channel (i.e. sparsification) by a chip level pre-equalizer filter which we call channel sparsifier, the effective channel after despreading presents itself as a symbol-level ISI channel. Time-varying equalization at symbol level is necessitated by the presence of aperiodic scrambler which is treated as deterministic. The optimal channel sparsifier maximizes SINR at the output of symbol level equalizer. We focus here on downlink channels that have significant dispersion in the temporal domain. Expressions for post processing SINRs (after channel sparsification, despreading and subsequent symbol level equalization) are derived for all receivers and used for performance evaluation. We show that improved receivers for WCDMA downlink can be designed benefiting from a combination of generalized channel sparsification, deterministic treatment of scrambler and non-linear equalization.

2times2 unitary preceding based on receiver feedback is applied alongside spatial multiplexing at the base station in HSDPA (D-TxAA) when the mobile terminal supports MIMO transmissions [1]. This precoding will influence achievable sum- rate of the MIMO channel if it influences the Signal-to- Interference-plus-Noise Ratio (SINR) of streams at the receiver (RX) output. We propose a set of MIMO HSDPA receivers, all based upon a LMMSE chip-level matrix filter (equalizer) front end, and introduce the notion of joint bias for the MIMO chip equalizer. Statistical properties of the spatial model thus obtained are exploited to analyze the performance of proposed MIMO receivers. It is shown that precoding choice depends upon the MIMO receiver and the extent of its impact depends on the MIMO RX.

We consider multicode and multirate transmission scenarios in a DS-CDMA system operating in an asynchronous fashion in a multipath environment. Oversampling wrt the chip rate is applied to the cyclostationary received signal and multisensor reception is considered, leading to a linear multichannel model. Channels for different users are considered to be finite-impulse response (FIR) and of possibly different lengths, depending upon their processing gains. We consider an individualized linear MMSE-ZF or projection receiver for a given user, exploiting its spreading sequence and timing information. In the multicode case, a certain user is considered to use several spreading codes in order to transmit at a higher rate. Considering different code sequences to be issuing from different virtual users, the propagation channel impulse responses of all these users are the same. However, the total channel impulse response which includes spreading sequences is different for all users. On the other hand, in the multirate case, a periodically varying set of periodic spreading codes spread successive symbols of a certain user. Symbols spread by different codes can therefore by considered to be issuing from different virtual users. The problem therefore boils down to classical multiuser detection with time-invariant interference canceling filters for each virtual user. A blind channel estimate is also obtainable through Capon's method (first used by Tsatsanis) as a by-product of the MMSE-ZF receiver algorithm.

We explore the channel estimation problem in the case of quasi-synchronous users in a DS-CDMA system. Knowledge of the transmit (TX) filter is assumed, and the anti-aliasing low-pass front end receive (RX) filter is designed for critical sampling at the Nyquist rate for the TX filter. It is shown that when the sampling frequency is larger than the Nyquist frequency, the discrete-time representation of the channel is not unique. However, all representations can be treated in a similar fashion once the Nyquist rate is satisfied. On the other hand, fractionally sampling the channel leads to a scenario in which the cut-off frequency can be approached arbitrarily close to the Nyquist rate. In the case of sparse channels, sampling the channel at any rate lends to a small number of non-zero coefficients in the finite-impulse response(FIR) representation of the channel. The structured channel estimation algorithm presented in this paper exploits the sparseness of this model. Results are compared with those of other previously proposed structured methods.

We address the problem of downlink interference rejection in a DS-CDMA system. Periodic orthogonal Walsh-Hadamard sequences spread different users' symbols followed by scrambling by a symbol aperiodic base-station specific overlay sequence. The point-to-point propagation channel from the cell-site to a certain mobile station is the same for all downlink signals (desired user as well as the intracell interference). Orthogonality of the underlying Walsh-Hadamard sequences is destroyed by multipath propagation, resulting in multiuser interference if a coherent combiner (the RAKE receiver) is employed. In this paper, we propose a blind linear equalization algorithm which equalizes for the common downlink channel, thus rendering the user signals orthogonal again. A simple code matched filter subsequently suffices to cancel the multiple access interference (MAI) from intracell users. It is shown that the receiver maximizes the signal-to-interference plus noise ratio (SINR) at its output.

We consider p users in a DS-CDMA system operating asynchronously in a multipath environment. Oversampling w.r.t. the chip rate is applied to the cyclostationary received signal and multi-antenna reception is considered, leading to a linear multichannel model. Channels for different users are considered to be FIR and of possibly different lengths. We consider an individualized linear MMSE receiver for a given user, exploiting its spreading sequence and timing information. The blind determination of the receiver boils down to the blind channel identification. We explore blind channel identifiability requirements. Sufficiency of these requirements is established and it is shown that if zero-forcing conditions can be satisfied, then the CDMA channel (and hence the receiver) is identifiable with probability 1. It is also shown that linear MMSE receivers obtained by different criteria (including a new one) have the same identifiability requirements asymptotically in SNR.

We study the performance and capacity of a quasi-synchronous code-division multiple-access (QS-CDMA) cellular system employing the decorrelating detector. It is assumed that each of N users has a GPS generated local clock, and attempts to transmit in synchrony with the other users in its cell. The detector makes use of the small timing uncertainties to build the interference signal space and perfectly cancel the interference. Results are compared with those of an adaptive MSE receiver. It is shown that when the LMS adaptive algorithm is employed, the mean-squared-error misadjustment significantly affects the receiver performance. Finally, system capacities in terms of users/cell are evaluated.