Reliable communication of data in modern wireless systems requires accurate channel state information (CSI). Sounding Reference Signal (SRS) based CSI acquisition enables the estimation of the channel between the base station and user equipment through the uplink transmission of known SRS by the user equipment to the base station. However, limited SRS resources and limited Signal to Noise Ratio (SNR) coverage for which SRS-based CSI acquisition can be performed renders the acquisition of CSI challenging. We propose an approach to perform sparse non-uniform SRS resource allocation and use a masked auto-encoder with a vision transformer backbone to reconstruct full band channel from partial sub-band information. Experiments on data emulating transmission over CDL-A, B, and C channels demonstrate that the proposed method can achieve state-of-the-art normalized mean square error (NMSE) using only 25% of the band information. This translates to a four fold increase in SRS resource capacity and 6dB improvement in SRS coverage under current 5G NR specifications.

Channel information is essential to unleash the benefits of 5G New Radio (NR) by enabling network intelligence that adapts transmissions to users’ channels. In this paper, we propose model-driven feature design and use support vector machine (SVM) to classify users’ speed range. Our model-driven features are designed based on stochastic channel modeling. Multiple features are derived from time-domain cross-correlation and time-domain auto-correlation function of the sounding reference signals. The classifier is trained and verified with extensive standard compliant simulation channels at different SNR levels and speeds, and attains greater than 90% accuracy.

Massive multi-input multi-output (MIMO) is shown to significantly increase spectral efficiency by exploiting a large number of antennas to support high-order multiuser MIMO. In 3GPP Release-13, a full-dimension MIMO (FD-MIMO) technology was introduced to address practical aspects for massive MIMO in cellular systems; extensive simulations show 2–4 times capacity gain compared with current LTE systems. FD-MIMO has been identified as one of the key 5G technologies and is being continuously improved in 3GPP new radio standards. However, several practical challenges such as interference mitigation among MIMO streams for a large number of users with limited channel feedback, hardware limitations, such as calibration errors that limit the precoding capabilities need to be addressed carefully. A proof of concept (PoC) base-station and user equipment (UE) prototype has been designed to validate the potential of FD-MIMO technology and demonstrate commercial implementation feasibility. In this paper, we present theory and architecture behind an FD-MIMO prototype and share the field test results with LTE-based UEs in a multi-user MIMO setup. We also analyze the impact of transmitter and receiver calibration errors on the performance of the FD-MIMO system.

To support downlink full-dimension (FD-MIMO) in FDD scenarios, an accurate yet reasonably efficient channel-state-information (CSI) feedback scheme is required to harness the potential beamforming gain offered by the use of a large number of antenna elements in a 2D active antenna array. In this paper, a reduced-spaced channel quantization and feedback scheme which exploits slow variation of the angle-of-departure (AoD) distribution is proposed. By perceiving the instantaneous spatial channel to be a linear combination of slowly varying subset of matrices, it is demonstrated that the proposed scheme offers up to 62.5% dimensionality reduction with negligible throughput loss in 16-antenna FD-MIMO system. When used together with vector quantization, the proposed scheme offers substantial gain over that supported by 3GPP LTE.

In a two-user broadcast channel where one user has full CSIR and the other has none, a recent result showed that TDMA is strictly suboptimal and a product superposition requiring non-coherent signaling achieves DoF gains under many antenna configurations. This work introduces product superposition in the domain of coherent signaling with pilots, demonstrates the advantages of product superposition in low-SNR as well as high-SNR, and established DoF gains in a wider set of receiver antenna configurations. Two classes of decoders, with and without interference cancellation, are studied. Achievable rates are established by analysis and illustrated by simulations.

Full-dimension multiple-input multiple-output (FD-MIMO) systems, in which base stations are equipped with a large number of antennas in a two-dimensional panel, has received considerable attention from academia researchers and industry practitioners. Compared with legacy cellular communication systems, FD-MIMO systems can achieve significantly higher spectral efficiency with high order multi-user MIMO (MU-MIMO) transmissions. However, as high-order MU-MIMO also incurs high precoding and scheduling complexity, it is critical to reduce complexity of these operations in order to realize throughput potential of FD-MIMO systems in practice. In this paper, we propose a reduced complexity algorithm to realize the high performance precoding technique, signal-to-leakage plus noise ratio (SLNR) precoding, and propose an efficient scheduling algorithm to enable high-order MU-MIMO transmissions in FD-MIMO systems. We further demonstrate the effectiveness of the proposed algorithms by using system level simulations.

In the fading MIMO broadcast channel, until recently the results under full CSIR and no CSIR indicated that degrees of freedom (DoF) cannot be improved beyond what is available via TDMA. Recently, however, it was discovered that when one node has full CSIR and the other has none, TDMA is no longer DoF-optimal and a product decomposition with noncoherent (Grassmannian) signaling achieves the optimal DoF under certain receiver antenna configurations. This work extends product superposition to the domain of coherent signaling with pilots, showing that it can also achieve the optimal DoF. In addition, this work demonstrates the advantages of product superposition in low-SNR as well as high-SNR, and extends the set of receiver antenna configurations under which product decomposition achieves optimal DoF.

We consider a spectrum-sharing network where n secondary relays are used to increase secondary rate and also mitigate interference on the primary by reducing the required overall secondary emitted power. We propose a distributed relay selection and clustering framework, obtain closed-form expressions for the secondary rate, and show that secondary rate increases proportionally to log n. Remarkably, this is on the same order as the growth rate obtained in the absence of a primary system and its imposed constraints. Our results show that to maximize the rate, the secondary relays must transmit with power proportional to n-1(thus the sum of relay powers is bounded) and also that the secondary source may not operate at its maximum allowable power. The tradeoff between the secondary rate and the interference on the primary is also characterized, showing that the primary interference can be reduced asymptotically to zero as n increases, while still maintaining a secondary rate that grows proportionally to log n. Finally, to address the rate loss due to half-duplex relaying in the secondary, we propose an alternating relay protocol and investigate its performance.

Interference alignment (IA) is known to significantly increase sum-throughput at high SNR in the presence of multiple interfering nodes, however, the reliability of IA is little known, which is the subject of this paper. We study the error performance of IA and compare it with conventional orthogonal transmission schemes. Since most IA algorithms require extensive channel state information (CSI), we also investigate the impact of CSI imperfection (uncertainty) on the error performance. Our results show that under identical rates, IA attains a better error performance than the orthogonal scheme for practical signal to noise ratio (SNR) values but is more sensitive to CSI uncertainty. We design bit loading algorithms that significantly improve error performance of the existing IA schemes. Furthermore, we propose an adaptive transmission scheme that not only considerably reduces error probability, but also produces robustness to CSI uncertainty.

This paper considers an uplink massive MIMO scheme that employs a pilot reuse scheme. For the massive MIMO scheme, a non-asymptotic cell throughput lower bound that is valid for any M is derived and the bound is shown to be tight by simulations. The lower bound is dependent upon three interference terms: intra-cell interference, inter-cell interference, and interference due to pilot contamination. A set of conditions on which each interference term dominates is examined by analysis and simulations, where the conditions are defined in terms of network topology, pilot reuse number and M. For example, for a dense network with M = 100, the largest cell throughput is achieved with pilot reuse number 2, in which case the traditional inter-cell interference dominates rather than the pilot contamination.

We consider a spectrum-sharing network where n secondary relays are used to increase the secondary rate. We propose a distributed amplify-and-forward (AF) relaying scheme combined with relay selection and clustering. For the proposed method we obtain a closed-form expression for the secondary rate, which shows that the rate grows proportionally to log n. Remarkably, this growth rate is on the same order as that achieved in the absence of a primary system and its imposed constraints. We find the optimal power strategy for the relays subject to primary constraints: to maximize the secondary rate, each of the selected relays need to transmit with power proportional to n-1(thus the sum of relay powers is bounded).

In multiantenna broadcast channels without channel state information at transmitter (CSIT), orthogonal transmission (e.g., TDMA) is known to achieve maximal degrees of freedom either with perfect channel state information at receiver (CSIR), or when no receiver has CSIR. Recently, it has been shown [1] that TDMA is no longer optimal in cases of unequal CSIR, e.g., when one receiver has CSIR and another does not. This paper proposes a multiplicative superposition that attains degrees of freedom uniformly higher than [1] and TDMA. The proposed scheme uses coherent signaling for the receiver with CSIR, and Grassmannian signaling for the receiver without CSIR. This signaling structure is shown to attain the optimal degrees of freedom under a wide set of antenna configurations.

Unlike point-to-point cognitive radio, where the constraint imposed by the primary rigidly curbs the secondary throughput, multiple secondary users have the potential to efficiently harvest the spectrum and share it among themselves. This paper analyzes the sum throughput of a multiuser cognitive radio system with multiantenna base stations, either in the uplink or downlink mode. The primary and secondary have N and n users, respectively, and their base stations have M and m antennas, respectively. We show that an uplink secondary throughput grows with m/N+1 log n if the primary is a downlink system, and grows with m/M+1 log n if the primary is an uplink system. These growth rates are shown to be optimal and can be obtained with a simple threshold-based user selection rule. In addition, we show that the secondary throughput can grow proportional to , while simultaneously the interference on the primary is forced down to zero, asymptotically. For a downlink secondary, it is shown that the throughput grows with in the presence of either an uplink or downlink primary system. In addition, the interference on the primary can be made to go to zero asymptotically, while the secondary throughput increases proportionally to . The effect of unequal path loss and shadowing is also studied. It is shown that under a broad class of path loss and shadowing models, the secondary throughput growth rates remain unaffected.

This paper considers the multiantenna broadcast channel without transmit-side channel state information. For this channel, it has been known that when all receivers have channel state information (CSIR), the degrees of freedom (DoFs) cannot be improved beyond what is available via time-division multiple access. The same is true if none of the receivers possess CSIR. This paper shows that an entirely new scenario emerges when receivers have unequal CSIR. In particular, orthogonal transmission is no longer DoF optimal when one receiver has CSIR and the other does not. A multiplicative superposition is proposed for this scenario and shown to attain the optimal DoFs under a wide set of antenna configurations and coherence lengths. Two signaling schemes are constructed based on the multiplicative superposition. In the first method, the messages of the two receivers are carried in the row and column spaces of a matrix, respectively. This method works better than orthogonal transmission while reception at each receiver is still interference-free. The second method uses coherent signaling for the receiver with CSIR, and Grassmannian signaling for the receiver without CSIR. This second method requires interference cancellation at the receiver with CSIR, but achieves higher DoF than the first method.

In a cognitive (secondary) multiple-access network which is subject to interference power constraints imposed by a primary system, it is desirable to mitigate the interference on the primary and to harvest multiuser diversity gains in the secondary. To simultaneously achieve these goals, a two-step (hybrid) scheduling method is proposed that pre-selects a set of secondary users based on their interference on the primary, and from among them selects the user(s) that yield the highest secondary throughput. The optimal number of active secondary transmitters is characterized as a function of the primary interference constraint, the secondary transmit power, and the number of secondary transmitters n. The secondary sum-rate (throughput) of the proposed algorithm grows optimally (proportional to log n). We investigate the tradeoff between scaling the secondary throughput and reducing interference on the primary, and characterize the optimum tradeoff in the regime of large n. Finally, we study user scheduling under fairness constraints, which is necessary when the channel statistics of secondary nodes are not identical. A modified hybrid scheduling rule is proposed to ensure user fairness, while still achieving the optimal growth rate for the secondary throughput.

This paper investigates the secondary multiuser diversity in spectrum sharing networks. We show that by exploiting the fading nature of interference links, the secondary system to efficiently utilize the spectrum while complying with constraints imposed by the primary system. More precisely, as the number of secondary users increases, the throughput grows logarithmically in a secondary multiple-access channel (MAC) and double-logarithmically in a secondary broadcast channel (BC). The multiuser diversity may also reduce the interference on the primary asymptotically to zero; the tradeoff between throughput enhancement and interference reduction is characterized. Finally, we results show that for the secondary MAC the growth rate of throughput decreases linearly with the number of primary users (constraints), while for the secondary BC the growth rate is unaffected by the number of primary constraints.

We consider the effective degrees of freedom (DoF) achieved by interference alignment when channel state information (CSI) is acquired by training and feedback. For a flat block- fading K × K interference channel with power P per transmitter and M antennas per node, we show that interference alignment achieves higher DoF than orthogonal transmission (e.g., TDMA) only if the channel coherence time is large and the capacity of feedback link is at least as Θ(log P). Under this condition, to maximize the effective DoF, each receiver needs to feed back CSI via (M2-1)log P bits per coherence interval; smaller growth rate of feedback bits will decrease the effective DoF. We also show that in the presence of training and feedback cost, K = 3 achieves the optimal DoF for a broad range of channel characteristics; with larger number of user pairs, the DoF falls short of its optimum and beyond a certain point becomes a decreasing function of K.

We consider a set of cognitive nodes cooperatively sensing the activities of a primary system. Two cooperative protocols are proposed, where cognitive nodes opportunistically transmit to each others, and finally each node makes a decision based its own observations. In the first protocol (Protocol 1), a node relays the signal received from the primary to the other nodes only if the signal energy is sufficiently large. In the second protocol (Protocol 2), given the knowledge of channel gains to the other nodes, a node transmits only if the channel gains are large. With two cognitive nodes, Protocol 1 improves the average detection probability by up to 50% relative to the protocol studied in. Compared to Protocol 1, while additional channel knowledge is needed, Protocol 2 saves up to 50% transmit power and maintains almost the same detection probability.

It is known that in multiantenna broadcast channels without transmitter-side channel state information (CSIT), time-sharing (orthogonal transmission) achieves the maximum multiplexing gain if perfect receiver-side channel state information (CSIR) is available to all receivers, or if no receiver has CSIR. We show that orthogonal strategies are not optimal in cases where some receivers have more CSIR than others. A superposition signaling is proposed to transmit to two receivers simultaneously on Grassmannians, achieving higher multiplexing gain compared with orthogonal transmissions. The information for the two receivers is conveyed by the row and column spaces of the transmitted matrix, respectively, which is constructed from a product of two matrices that each lie on different Grassmannians. This multiplicative superposition allows the two receivers to be interference-free from the other's signals even without CSIT.