Device-to-device (D2D) communication using 5G New Radio (NR) sidelink (SL) is envisioned to be a key enabler of high speed, low latency applications, with automated driving being the prime use case. To meet the high data rate requirements, it is essential for SL devices to be able to operate in mmWave/sub-THz frequencies where bandwidth is abundant. Consequently, several enhancements will be needed to the current version of NR SL, which is mainly designed for sub-6 GHz frequencies. Beamforming based highly directional transmission/reception used at high carrier frequencies result in directional deafness in other directions. For SL UE autonomous resource allocation, termed as Mode 2 of NR SL in 3GPP, this results in a UE’s inability to detect transmissions not aligned to its primary direction of reception, which leads to high packet errors. In this paper, we focus on system wide performance of 3GPP based NR SL Mode 2 resource allocation for directional systems at mmWave/sub-THz frequencies. We propose a composite strategy that comprises paired SL control transmission and sensing, whereby SL UEs transmit and receive the SL control information in an additional “paired” direction, directly opposite to their intended direction of transmission. This helps eliminate hidden node interference while avoiding too many exposed nodes. System level simulations in NR V2X highway scenarios show significant performance improvement of the proposed scheme over conventional solutions like omnidirectional or directional transmission/reception of SL control information.

In unlicensed spectrum, a 5G device is required to access to a channel by using load based equipment (LBE) where it does channel sensing whenever it has data to transmit or frame based equipment (FBE) where it only does channel sensing per fixed period. The devices using LBE and FBE can coexist in the 5G network. Therefore, this paper provides a Markov chain model to analyze the system where the LBE devices and the FBE devices coexist. Subsequently, based on channel access time and transmission probability from the Markov chain model, we propose that the devices are able to switch dynamically from FBE to LBE to serve data with high priority such as Ultra-reliable low-latency communication or data with high arrival rate and from LBE to FBE to serve data with low priority such as Enhanced mobile broadband or data with low arrival rate. The numerical results show the benefits of the dynamic switch between LBE and FBE in reducing channel access time for high priority data and energy consumption for low priority data.

The 3rd Generation Partnership Project (3GPP) has defined Ultra-Reliable Low-Latency Communication (URLLC) as one of the main objectives of 5G development to satisfy the applications with stringent requirements of latency and reliability. Uplink (UL) configured-grant (CG) transmission where the user equipment (UE) transmits a packet without scheduling request (SR) and UL grant is standardized by 3GPP Release 15 to reduce latency. The UE also transmits automatically a configured number of repetitions without feedback from the base station (gNB) to increase reliability.Nevertheless, the repetitions are not allowed to transmit outside the hybrid automatic repeat request (HARQ) process containing the first repetition. It might cause a smaller number of transmitted repetitions than configuration that is harmful to the performance of URLLC.This paper uses the reserved resources where the UEs can transmit the repetitions outside the original HARQ process until the configured number is reached. The scheme is developed further when the gNB is equipped with a successive interference cancellation (SIC) receiver so it can decode multiple repetitions of the different UEs in the same reserved resource. The use of reserved resources ensures the performance of UL CG transmission while SIC receiver minimizes the reserved resource's consumption. The numerical results show a higher transmission reliability and lower reserved resource consumption of the proposed scheme compared to the related works.

Ultra-reliable low-latency communication (URLLC) is one of the main services in 5G New Radio (NR) to serve the applications with the strict requirements of latency and reliability. Increase of mobile traffic and bandwidth requirements for new applications have resulted in a shortage of licensed spectrum so that even URLLC services are deemed to be running over the unlicensed spectrum. This may require a significant re-design of channel access, transmission and reception procedures over the unlicensed spectrum and is currently being investigated in The 3rd Generation Partnership Project (3GPP) Release 17.This paper focuses on the channel access mechanism for URLLC services over the unlicensed spectrum. It provides an analytical analysis of current channel access procedures, listen before talk (LBT). LBT states in random duration channel access are modeled through Markov chains which help characterize the closed form expressions for average channel access time. These expressions are evaluated using the parameters from currently standardized channel access priority classes. The evaluation shows the total inability of several current channel access classes to support URLLC services over the unlicensed spectrum even under low load conditions.The insights gained from this analysis lead the proposal of new channel access priority classes where new special classes are introduced for URLLC services. The results are provided demonstrating the improved performance of URLLC services in the unlicensed spectrum with the proposed changes in the channel access procedures.

In uplink (UL) transmission, the Ultra-Reliable Low-Latency Communication (URLLC) users (UEs) might be assigned the grant-free (GF)/configured-grant (CG) periodic resources to transmit data straightaway instead of sending scheduling request (SR) and receiving UL grant. However, when these resources are not in use by the URLLC traffic, the base station (called gNB) can dynamically schedule the Enhanced Mobile Broadband (eMBB) UEs to transmit in the GF resources to increase the resource efficiency. This may lead to potential collision and detrimental QoS for URLLC as some of the URLLC UEs may become active and try to use the same resource assigned to an eMBB UE. In this paper, a two-step strategy containing an overlap indication and explicit Hybrid automatic repeat request (HARQ) feedback is proposed to improve URLLC performance in multiplexing with eMBB. Besides the explicit HARQ feedback structure, a scheme with an additional SR is also presented. Simulation results show that these two schemes help achieving URLLC requirements by reducing error probability due to Demodulation Reference Signal (DMRS) miss-detection while allowing better resource efficiency.

Ultra-dense small cell networks will require sophisticated user association algorithms that consider (i) channel characteristics, (ii) base station load, and (iii) uplink/downlink (UL/DL) traffic profiles. They will also be characterized by high spatio-temporal variability in UL/DL traffic demand, due to the fewer users per BS. In this direction, Dynamic TDD is a promising new technique to match BS resources to actual demand. While plenty of literature exists on the problem of user association, and some recent on dynamic TDD, most works consider these separately. In this paper, we argue that user association policies are strongly coupled with the allocation of resources between UL and DL. We propose an algorithm that decomposes the problem into separate subproblems that can each be solved efficiently and in a distributed manner, and prove convergence to the global optimum. Simulation results suggest that our approach can improve UL and DL performance at the same time, with an aggregate improvement of more than 2×, compared to user association under static TDD allocation.

Operators, struggling to continuously add capacity and upgrade their architecture to keep up with data traffic increase, are turning their attention to denser deployments that improve spectral efficiency. Denser deployments make the problem of user association challenging, and much work has been devoted to finding algorithms that strike a tradeoff between user quality of service, and network-wide performance (load-balancing). Nevertheless, the majority of these algorithms typically consider simple setups with a single type of traffic, usually elastic non-guaranteed bit rate (GBR). They also focus on the radio access part, ignoring the backhaul topology and potential capacity limitations. Backhaul constraints are emerging as a key performance bottleneck in future networks, partly due to the continuous improvement of the radio interface, and partly due to the need for inexpensive backhaul links to reduce capital and operational expenditures. To this end, we propose an analytical framework for user association that jointly considers radio access and backhaul network performance. Specifically, we derive an algorithm that takes into account spectral efficiency, base station load, backhaul link capacities and topology, and two traffic classes (GBR and non-GBR) in both the uplink and downlink directions. We prove analytically an optimal user association rule that ends up maximizing either an arithmetic or a weighted harmonic mean of the achieved performance along different dimensions (e.g., uplink and downlink performances or GBR and non-GBR performances). We then use extensive simulations to study the impact of: 1) traffic differentiation; and 2) backhaul capacity limitations and topology on key performance metrics.

Operators, struggling to continuously add capacity and upgrade their architecture to keep up with data traffic increase, are turning their attention to denser deployments that improve spectral efficiency. Denser deployments make the problem of user association challenging, and much work has been devoted to finding algorithms that strike a tradeoff between user quality of service (QoS), and network-wide performance (load-balancing). Nevertheless, the majority of these algorithms typically consider only the radio access part, and ignore the backhaul topology and potential capacity limitations. Backhaul constraints are emerging as a key performance bottleneck in future heterogeneous networks, partly due to the continuous improvement of the radio interface, and partly due to the need for inexpensive backhaul links to reduce CAPEX/OPEX. To this end, we propose an analytical framework for user association that jointly considers radio access and backhaul performance. We derive an algorithm that takes into account spectral efficiency, base station load, backhaul link capacities and topology, and uplink and downlink traffic demand, and prove it converges to an optimal solution. We then use extensive simulations to study the impact of (i) backhaul capacity limitations and (ii) backhaul topology on key performance metrics.

The widespread adoption of tablets and smartphones, and an abundance of data-hungry mobile applications, are overwhelming wireless networks with increased demand and introduce considerable traffic diversity. Operators struggling to continuously add capacity and upgrade their architecture have resorted instead to building denser deployments to improve spectral efficiency. By increasing the number of cells a user can associate with, (i) user quality of service (QoS) can be improved, and (ii) traffic can be offloaded from congested base stations, to achieve better load balancing. However, these two goals are not always aligned. To this end, we develop an analytical framework for optimal user association in future HetNets that investigates the potential tradeoffs between user- and network-related performance, in a more realistic setup encompassing additional key features: (i) different types of user flows, and (ii) uplink and downlink performance. We believe this better reflects the diversity of the services offered to users and their impact on system performance. We evaluate our proposed framework through extensive simulations, and provide some qualitative and quantitative insights on the related tradeoffs.

International audience

Obtaining accurate Channel State Information (CSI) at multiple Transmitters (TXs) is critical to the performance of many cooperative transmission schemes, including joint precoding in the context of network MIMO. Practical CSI feedback and limited backhaul-based sharing creates degradations of CSI which are specific to each TX, giving rise to a Distributed (D-) CSI configuration. In the D-CSI broadcast channel setting, each TX implements separate elements of the joint multi-user precoder based on its own individual CSI estimate. In this work, we presents a first finite-SNR regime rate analysis for a network-MIMO (broadcast channel) under a distributed CSI setting. Of particular importance is the notion of a “price of distributedness” which penalizes the D-CSI setting over the conventional centralized one with the same overall feedback quality. To tackle this problem, we apply tools from the field of Random Matrix Theory (RMT) to derive deterministic equivalents of the Signal to Interference plus Noise Ratio (SINR) for a popular class of precoders. Our key finding lies in the notion that the price of distributedness converges to a predictable value, bounded away from zero, as the number of antennas grows.1

Small cell networks (SCNs) are widely considered as a promising solution for future cellular deployments. Lately, the benefits of small cells to improve spectrum utilization and the user quality of experience (QoE) have been well documented. In addition, the power consumption of current deployments, for instance due to idle power and cooling equipment, is a major concern for operators. Small cells offer the opportunity for more dynamic power management of base stations, due to coverage overlaps and larger spatio-temporal load fluctuations. Yet, such power management decisions (e.g. turning off a base station) should not lead to excessive performance degradation for users associated with it or additional power consumption. This tradeoff becomes significantly more challenging to evaluate in future networks, due to the diversity of services offered to users beyond the traditional voice calls, as well as the complexity of traffic scheduling algorithms. The goal of this paper is to make a first step towards an analytical investigation of this tradeoff. To this end, we propose a number of QoE constraints that a power management decision should consider, and analytically relate them to key parameters such as user traffic mix, cell load, user density, etc. We then use this framework to perform a preliminary study of the potential energy savings an operator could achieve, while guaranteeing the satisfaction of these constraints. Our results provide some qualitative and quantitative insights on the interesting tradeoff between switch-off duration and number of small cells one can safely switch off.

This paper considers the two-user Gaussian Causal Cognitive Interference Channel (GCCIC), which consists of two source-destination pairs that share the same channel and where one full-duplex cognitive source can causally learn the message of the primary source through a noisy link. The GCCIC is an interference channel with unilateral source cooperation that models practical cognitive radio networks. Different achievable strategies are shown to be at most a finite number of bits away from an outer bound for a set of the channel parameters that, roughly speaking, excludes the case of weak interference at both receivers.

This paper studies the two-user interference channel with unilateral source cooperation, which consists of two source-destination pairs that share the same channel and where one full-duplex source can overhear the other source through a noisy in-band link. Novel outer bounds of the type 2R1+ R2and R1+ 2R2are developed for the class of injective semi-deterministic channels with independent noises at the different source-destination pairs. The bounds are then specialized to the Gaussian noise case. Interesting insights are provided about when these types of bounds are active, or in other words, when unilateral cooperation is too weak and leaves some system resources underutilized.

This paper studies the two-user Gaussian interference channel with half-duplex causal cognition. This channel model consists of two source-destination pairs sharing a common wireless channel. One of the sources, referred to as the cognitive, overhears the other source, referred to as the primary, through a noisy link and can therefore assist in sending the primary's data. Due to practical constraints, the cognitive source is assumed to work in half-duplex mode, that is, it cannot simultaneously transmit and receive. This model is more relevant for practical cognitive radio systems than the classical information theoretic cognitive channel model, where the cognitive source is assumed to have a non-causal knowledge of the primary's message. Different network topologies are considered, corresponding to different interference scenarios: (i) the interference-symmetric scenario, where both destinations are in the coverage area of the two sources and hence experience interference, and (ii) the interference-asymmetric scenario, where one destination does not suffer from interference. For each topology the sum-rate performance is studied by first deriving the generalized Degrees of Freedom (gDoF), or "sum-capacity pre-log" in the high-SNR regime, and then showing relatively simple coding schemes that achieve a sum-rate upper bound to within a constant number of bits for any SNR. Finally, the gDoF of the channel is compared to that of the non-cooperative interference channel and to that of the non-causal cognitive channel to identify the parameter regimes where half-duplex causal cognition is useless in practice or attains its ideal ultimate limit, respectively.

This paper considers the two-user Gaussian causal cognitive interference channel (GCCIC), which consists of two source-destination pairs that share the same channel and where one full-duplex cognitive source can causally learn the message of the primary source through a noisy link. The GCCIC is an interference channel with unilateral source cooperation that better models practical cognitive radio networks than the commonly used model which assumes that one source has perfect noncausal knowledge of the other source's message. First, the sum-capacity of the symmetric GCCIC is determined to within a constant gap. Then, the insights gained from the study of the symmetric GCCIC are extended to more general cases. In particular, the whole capacity region of the Gaussian Z-channel, i.e., when there is no interference from the primary user, and of the Gaussian S-channel, i.e., when there is no interference from the secondary user, are both characterized to within 2 bits. The fully connected general, i.e., no-symmetric, GCCIC is also considered and its capacity region is characterized to within 2 bits when, roughly speaking, the interference is not weak at both receivers. The parameter regimes where the GCCIC is equivalent, in terms of generalized degrees-of-freedom, to the noncooperative interference channel (i.e., unilateral causal cooperation is not useful), to the non-causal cognitive interference channel (i.e., causal cooperation attains the ultimate limit of cognitive radio technology), and to bilateral source cooperation are identified. These comparisons shed light into the parameter regimes and network topologies that in practice might provide an unbounded throughput gain compared to currently available (non cognitive) technologies.

This paper considers the Gaussian half-duplex relay channel (G-HD-RC): a channel model where a source transmits a message to a destination with the help of a relay that cannot transmit and receive at the same time. It is shown that the cut-set upper bound on the capacity can be achieved to within a constant gap, regardless of the actual value of the channel parameters, by either partial-decode-and-forward or compress-and-forward. The performance of these coding strategies is evaluated with both random and deterministic switch at the relay. Numerical evaluations show that the actual gap is less than what analytically obtained, and that random switch achieves higher rates than deterministic switch. As a result of this analysis, the generalized degrees-of-freedom of the G-HD-RC is exactly characterized for this channel. In order to get insights into practical schemes for the G-HD-RC that are less complex than partial-decode-and-forward or compress-and-forward, the exact capacity of the linear deterministic approximation (LDA) of the G-HD-RC at high signal-to-noise-ratio is determined. It is shown that random switch and correlated nonuniform inputs bits are optimal for the LDA. It is then demonstrated that deterministic switch is to within one bit from the capacity. This latter scheme is translated into a coding strategy for the original G-HD-RC and its optimality to within a constant gap is proved. The gap attained by this scheme is larger than that of partial-decode-and-forward, thereby pointing to an interesting practical tradeoff between gap to capacity and complexity.

This paper considers a Gaussian relay network where a source transmits a message to a destination with the help of N half-duplex relays. The information theoretic cut-set upper bound to the capacity is shown to be achieved to within 1.96(N+2) bits by noisy network coding, thereby reducing the previously known gap. This gap is obtained as a special case of a more general constant gap result for Gaussian half-duplex multicast networks. It is then shown that the generalized degrees-of-freedom of this network is the solution of a linear program, where the coefficients of the linear inequality constraints are proved to be the solution of several linear programs referred as the assignment problem in graph theory, for which efficient numerical algorithms exist. The optimal schedule, that is, the optimal value of the 2Npossible transmit-receive configuration states for the relays, is investigated and known results for diamond networks are extended to general relay networks. It is shown, for the case of N=2 relays, that only N+1=3 out of the 2N=4 possible states have a strictly positive probability and suffice to characterize the capacity to within a constant gap. Extensive experimental results show that, for a general N -relay network with N≤8 , the optimal schedule has at most N+1 states with a strictly positive probability. As an extension of a conjecture presented for diamond networks, it is conjectured that this result holds for any half-duplex relay network and any number of relays. Finally, a network with N=2 relays is studied in detail to illustrate the channel conditions under which selecting the best relay is not optimal, and to highlight the nature of the rate gain due to multiple relays.

This paper considers the causal cognitive interference channel that consists of two full-duplex transmitter-receiver pairs sharing the same channel, where one transmitter can causally learn the message of the other transmitter through a noisy link. This channel models unilateral source cooperation. The work focuses on the generalized degrees-of-freedom of the symmetric, i.e. the two interfering links and the two direct links have the same strength, sum-capacity for the Gaussian noise channel. It is shown through evaluation of various achievable schemes that known sum-rate upper-bounds are achievable to within a constant gap regardless of the strength of the channel parameters. The achievable schemes are quite simple in the sense that only superposition coding is used, while it is shown that more complex schemes using binning can achieve a smaller gap.

This paper considers the Gaussian relay channel where the relay node operates in half-duplex mode. The exact capacity of the linear deterministic approximation of the Gaussian channel at high SNR is derived first. This result is then used to inspire an achievable scheme valid for any SNR in the original channel. The scheme is quite simple: it uses successive decoding and does not incur in the typical delay of backward decoding. The achievable rate is then showed to be at most 3 bits away from the cut-set upper bound, which allows to analytically determine the generalized Degrees-of-Freedom of the channel. A closed form expression for the gDoF-optimal fraction of time the relay node transmits is found as well.

This paper studies the Gaussian half duplex relay channel, where the relay node can not transmit and receive at the same time. The main contribution lies in showing that both Partial-Decode-Forward and Compress-Forward achieve the CutSet upper bound to within a constant gap regardless of the channel parameters. This provides a closed form characterization of the Generalized Degrees-of-Freedom (gDoF) of the channel, which for certain channel parameters is strictly smaller than the gDoF of the full duplex channel. Half duplex channels can convey information through the random switch between the receive and retransmit phases; this work shows numerically that random switch achieves larger rates compared to deterministic switch, which is usually considered in the literature.

This paper studies the sum-capacity of the Gaussian half-duplex causal cognitive interference channel, a channel model with two transmitter-receiver pairs where a (cognitive) source cooperates with the other (primary) source in sending data through a shared channel. In contrast to the classical cognitive radio model, here the cognitive source can not transmit and receive at the same time and must causally learn the primary message through a noisy channel. Achievable strategies are developed and shown to match known upper bounds on the symmetric sum-capacity of this channel to within a constant gap for all values of channel parameters. In the process, the generalized degrees of freedom of the channel is characterized.

This paper studies a Gaussian relay network, where the relays can either transmit or receive at any given time, but not both. Known upper (cut-set) and lower (noisy network coding) bounds on the capacity of a memoryless full-duplex relay network are specialized to the half-duplex case and shown to be to within a constant gap of one another. For fairly broad range of relay network sizes, the derived gap is smaller than what is known in the literature, and it can be further reduced for more structured networks such as diamond networks. It is shown that the asymptotically optimal duration of the listen and transmit phases for the relays can be obtained by solving a linear program; the coefficients of the linear constraints of this linear program are the solution of certain `assignment problems' for which efficient numerical routines are available; this gives a general interesting connection between the high SNR approximation of the capacity of a MIMO channel and the `assignment problem' in graph theory. Finally, some results available for diamond networks are extended to general networks. For a general relay network with 2 relays, it is proved that, out of the 4 possible listen/transmit states, at most 3 have a strictly positive probability. Numerical results for a network with K - 2 <; 9 relays show that at most K-1 states have a strictly positive probability, which is conjectured to be true for any number of relays.

Multi-user transmission, enabled through spatial multiplexing, is a promising technique in wireless systems by sending information to more than one user on a common resource block. Although efficient, precise channel information is needed in order to minimize the possible interferences. Motivated by its importance, the study investigates interference management in multi-user downlink systems under heterogeneous feedback of channel state information to the transmitter (CSIT). In the considered scenario, the base station (BS) can obtain different levels of channel realization information from the users under multi-user transmission. In particular we focus on a generic scenario with two user equipments (UEs), one (UE-1) being able to provide a perfect CSIT to the BS and the other (UE-2) unable to, where an effective transmission strategy at the BS is proposed with the premise of mitigating interference at UE-1. Unfortunately the absence of CSIT for UE-2 pushes it in interference-limited regime. To this end, two approaches are considered in the study: one by developing additional spatial diversity, and the other via advanced receiver design at UE-2. We investigate both of the options and show that the rate of UE-2 gets significantly improved in both cases. However hardware and RF design constraints may make the advanced receiver design solution preferable over the spatial diversity solution. We then put this heterogeneous CSIT feedback system in the context of long term evolution (LTE) of third generation partnership project (3GPP) where interference cannot be nulled out even for UE-1 due to the feedback of low level quantized CSIT and the restriction of the use of a very limited set of beamformers. The paper demonstrates that the advanced interference-aware receiver design can bring significant gains in the considered scenario, thereby underlining the necessity of intelligent receiver-processing in modern wireless systems.

In an underlay Cognitive Radio Network, multiple secondary users coexist geographically and spectrally with multiple primary users under a constraint on the maximum received interference power at the primary receivers. Given such a setting, one may ask “how to achieve maximum utility benefit at the secondary users given the imposed interference temperature constraint”? In an attempt at answering this question, we introduce a measure of the marginal secondary utility per unit primary interference (termed as relative rate utility) and propose a distributed algorithm that tries to maximize this measure. We present selected computer based Monte-Carlo simulation results, demonstrating the effectiveness of the introduced measure, and the improved performance of the proposed algorithm.

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.

The communication between a multiple-antenna transmitter and multiple receivers (users) with either a single or multiple-antenna each can be significantly enhanced by providing the channel state information at the transmitter (CSIT) of the users, as this allows for scheduling, beamforming and multiuser multiplexing gains. The traditional view on how to enable CSIT has been as follows so far: In time-division duplexed (TDD) systems, uplink (UL) and downlink (DL) channel reciprocity allows for the use of a training sequence in any given uplink slot, which is exploited to obtain an uplink channel estimate. This estimate is in turn recycled in the next downlink slot. In frequency-division duplexed (FDD) systems, which lack the UL and DL reciprocity, the CSIT is provided via the use of a dedicated feedback link of limited capacity between the receivers and the transmitter. In this paper, we focus on TDD systems and show that the traditional TDD CSIT acquisition fails to fully exploit the channel reciprocity in its true sense. In fact, we show that the system can benefit from a combined CSIT acquisition strategy mixing the use of limited feedback and that of a training sequence. We demonstrate the potential of our approach in terms of improved CSIT quality under a global training and feedback resource constraint.

The absolute gain of multi-user diversity in the context of a downlink channel is the focus of this contribution. Enjoying multi-user diversity gain first requires the channel information availability at the transmitter (CSIT) in a normal downlink (DL) system. Although multi-user diversity gains have been specified well, but the burden of exchange of information required is not rigorously accounted for. We analyze a time-division duplex (TDD) broadcast channel with initial assumption of channel information neither at the base station (BS) nor at the users' side. We propose two different but simple transmission strategies which make necessary channel state information (CSI) available at both communicating ends. We give approximate analytical expressions for both strategies which capture well the resource utilization (the cost) and the gain associated to multi-user diversity. This helps us to analyze the absolute gain of the multi-user diversity. The two schemes, the one with oblivious users and the other with informed users, are compared for the sum rate and interesting conclusions are drawn.

In this paper, we consider stationary time- and frequency-selective MIMO channels. No channel knowledge neither at the transmitter nor at the receiver is assumed to be available. We investigate the capacity behavior of these doubly selective channels as a function of one of the system parameters, the number of transmit antennas and channel parameters as delay spread, Doppler bandwidth and channel spread factor (the product of the previous two parameters). For critically spread channels (channel spread factor of 1), it is widely believed that the dominant term of high-SNR expansion of the capacity is log(log(SNR)) or in other words, the pre-log (the coefficient of log(SNR)) is zero. We provide a very simple scheme showing that for critically spread and mildly overspread channels a non-zero pre-log exists under certain conditions. We specify these conditions in terms of the Doppler bandwidth and the delay spread. We reason that for nearly critically spread channels, MIMO systems exhibit same degrees of freedom as that of a SISO system. At higher channel spread factor (overspread case), the log(SNR) term vanishes and log(log(SNR)) term becomes the dominant capacity term. We specify the range of existence for log(SNR) regime.

The asymptotic capacity for the non-coherent MIMO stationary channels having nttransmit and nrreceive antennas with flat fading is the focus of this paper. Fading processes of concern are bandlimited. These non-coherent MIMO channels were studied by Etkin and Tse and lower bound of capacity was shown to grow with min(nt, nr)[1 - min(nt, nr)mu] log(SNR) where mu is the normalized Doppler bandwidth. The contribution of this paper is to specify the pre-log for MIMO channels and this is done by giving matching upper and lower bounds of the pre-log. Moreover min(nt, nr) factor in the pre-log term bears a small modification. The actual pre-log is min(nt, nr, 1/2mu)[1 - min(nt, nr, 1/2mu)mu] and takes into account the optimal number of streams that should be activated as a function of the Doppler bandwidth.

This paper investigates the problem of channel quality indicator (CQI) estimation in the context of OFDMA systems in the downlink. The problem of CQI estimation is addressed for SINR-based CQI forms. In this paper, we present a technique for instantaneous SINR estimation which consists in using the channel estimator already present at the receiver to obtain the useful signal levels and signal regeneration (SR) estimator to get the level of interference plus noise. We show that SR estimator has an error floor caused by channel estimation errors, and then we introduce a compensation factor rho in order to remove this error floor. The compensation factor rho is defined as the ratio between the variance of channel estimation errors and the level of interference plus noise at the input of the channel estimator. Thanks to the compensation factor rho we achieve a gain of about 1 dB in term of RMSE for CQI estimation over a wide range of CQI values.