Integrated Access and Backhaul (IAB) represents a fast and cost-efficient network deployment technology that enhances the coverage of millimeter-wave (mmWave) 5G networks. In addition to the conventional challenges of wireless multi-hop relaying such as, e.g., increased interference and packet delays, traffic asymmetry can lead to significant delay degradation. While centralized coordination can mitigate these challenges, it may also lead to unnecessary overheads. In this paper, we propose an effective delay-aware distributed solution for joint access and backhaul link scheduling and route selection designed to function with limited information, which relies only on the knowledge collected from immediate neighbors. We formulate the joint upstream and downstream routing and scheduling problem, which is solved in a distributed manner for the IAB system with diverse delay requirements. To effectively tackle this problem, we employ deep reinforcement learning (DRL) algorithms. Our numerical results demonstrate that the proposed distributed solution provides improved scalability as compared to the centralized approach without a significant performance loss.

The use of millimeter-wave (mmWave) frequencies by 5G/5G+ technology results in increased signal attenuation naturally requiring dense network deployments. However, traditional fiber-based backhauling proves costly for network operators. To address this issue, 3GPP proposed the Integrated Access and Backhaul (IAB) concept to enable wireless backhaul and reduce deployment costs. However, system dynamics such as user mobility and traffic variations challenge system optimization and may shift the performance from its optimized state. On top of this, in-band mmWave IAB networks are subject to the half-duplex constraint, which prevents simultaneous transmission and reception. These limitations present challenges in optimizing the IAB network. Therefore, the goal of this study is to provide a computationally-efficient methodology for resource allocation and user scheduling in mm Wave IAB networks considering the aforementioned system limitations and constraints. Moreover, we evaluate the influence of system-specific factors and dynamics on the optimization of IAB networks and the time that it takes for the system to deviate from its optimized state. Our results show that by employing an optimally-parametrized scheduler, the throughput gain is 55% as compared to the baseline, where the radio resources are split equally among the users. The cell size is the primary parameter affecting the optimization gain, i.e., smaller cell sizes result in diminishing benefits when utilizing optimized algorithms.

Recently proposed by 3GPP, Integrated Access and Backhaul (IAB) technology promises to deliver a cost-efficient and flexible solution for network densification in 5G/6G systems. Since IAB architecture is based on multi-hop topology and advanced functionalities, such as multi-connectivity transmission and multi-routing, the potential utilization of IAB systems raises an issue of efficient system design. In this paper, we develop an optimization framework capable of jointly selecting transmission paths and allocating radio resources in compliance with half-duplexing and interference constraints. The presented numerical results illustrate that directional mm Wave beams employed at the wireless backhaul are essential for capacity boosting, thus allowing to fully exploit the radio resources in self-backhauled systems. We also establish that the multi-hop IAB topology provides advantages in terms of end-to-end user throughput as compared to single-hop systems.

Modern wireless infrastructures provide multiple options for a transmitter to utilize multiple independent data paths. Examples include simultaneous connections via multiple radio access technologies (multi-RAT), dual/multi-connectivity and carrier aggregation in 5G, Integrated Access and Backhaul (IAB) network, etc. Such network redundancies can be utilized to provide enhanced reliability and/or delay performances over the wireless media, e.g., to support ultra-reliable low-latency (URLLC) services. However, traditional reliability enhancement techniques fall short of making efficient use of such multi-path transmission environments. Packet-level coding, in this case, can be a better candidate to support URLLC since it provides enhanced reliability with higher spectral efficiency and low latency by proactively adding coded redundancy, which also enables the effective treatment of all paths as a single data pipe. As the multi-path scenarios are oftentimes heterogeneous in terms of supported data rate, packet-level reliability, transmission delay, etc., how to optimally design the coding parameters to achieve URLLC requirements becomes an issue. In this paper we study the problem of minimizing the transmission delay while meeting the required reliability target in the multi-path environment. We assume the packets arrive in bursts and linear packet-level coding is used to enhance reliability. We propose a fast bisection algorithm to determine the optimal code rate and path traffic distribution rule for the encoded packets, which provably achieves the minimum delay with the required reliability under very general conditions.

The high propagation losses and sensitivity to link blockage naturally require dense deployments of millimeter-wave (mmWave) 5G New Radio (NR) systems. One of the inherent challenges in these deployments is cost-efficient backhauling. Addressing this issue, 3GPP has recently proposed the concept of integrated access and backhaul (IAB) to reduce the deployment costs by enabling wireless backhaul. The efficient utilization of spectrum in these systems is conditional on the ability of IAB nodes to simultaneously receive signals on their sectoral antennas. In this paper, we investigate the interference caused by this functionality and identify countermeasures including angular and spatial diversities. Our numerical results demonstrate that the angular distance of 25° between the user equipment (UE) served by adjacent sectoral antennas is sufficient to efficiently mitigate interference. A comparable reduction in the interference level can also be achieved by utilizing spatial diversity with antenna separation of at least 20 m. By combining these methods, one can identify the target levels of angular and spatial diversities suitable for the particular deployment restrictions.

Connection management is an important problem for any wireless network to ensure smooth and well-balanced operation throughout. Traditional methods for connection management (specifically user-cell association) consider sub-optimal and greedy solutions such as connection of each user to a cell with maximum receive power. However, network performance can be improved by leveraging machine learning (ML) and artificial intelligence (AI) based solutions. The next generation software defined 5G networks defined by the Open Radio Access Network (O-RAN) alliance facilitates the inclusion of ML/AI based solutions for various network problems. In this paper, we consider intelligent connection management based on the O-RAN network architecture to optimize user association and load balancing in the network. We formulate connection management as a combinatorial graph optimization problem. We propose a deep reinforcement learning (DRL) solution that uses the underlying graph to learn the weights of the graph neural networks (GNN) for optimal user-cell association. We consider three candidate objective functions: sum user throughput, cell coverage, and load balancing. Our results show up to 10% gain in throughput, 45-140% gain cell coverage, 20-45% gain in load balancing depending on network deployment configurations compared to baseline greedy techniques.

With multiple radio access technologies such as Wi-Fi, LTE, 5G available at the edge, increasingly prevalent multi-radio end devices can establish multiple concurrent connections with the edge server to deliver data traffic with more bandwidth, lower latency and higher reliability. To fully harvest multi-connectivity benefits, the edge network requires intelligent traffic management to efficiently utilize radio resources as well as to optimize quality-of-service (QoS) metrics. This paper presents a general framework for multi-connectivity traffic management at the edge, and provides algorithms for routing traffic over multiple paths to enhance the latency QoS metric. Simulation results demonstrate that, with two concurrent radio connections such as LTE and WiFi, our proposed edge traffic management algorithm can achieve significant latency reduction by more than 4× for the 95-th packet latency, and 23× in delay violation rate reduction given 10 ms latency target when compared to state-of-the-art client-based traffic management solutions.

Federated learning enables training a global model from data located at the client nodes, without data sharing and moving client data to a centralized server. Performance of federated learning in a multi-access edge computing (MEC) network suffers from slow convergence due to heterogeneity and stochastic fluctuations in compute power and communication link qualities across clients. We propose a novel coded computing framework, CodedFedL, that injects structured coding redundancy into federated learning for mitigating stragglers and speeding up the training procedure. CodedFedL enables coded computing for non-linear federated learning by efficiently exploiting distributed kernel embedding via random Fourier features that transforms the training task into computationally favourable distributed linear regression. Furthermore, clients generate local parity datasets by coding over their local datasets, while the server combines them to obtain the global parity dataset. Gradient from the global parity dataset compensates for straggling gradients during training, and thereby speeds up convergence. For minimizing the epoch deadline time at the MEC server, we provide a tractable approach for finding the amount of coding redundancy and the number of local data points that a client processes during training, by exploiting the statistical properties of compute as well as communication delays. We also characterize the leakage in data privacy when clients share their local parity datasets with the server. Additionally, we analyze the convergence rate and iteration complexity of CodedFedL under simplifying assumptions, by treating CodedFedL as a stochastic gradient descent algorithm. Finally, for demonstrating gains that CodedFedL can achieve in practice, we conduct numerical experiments using practical network parameters and benchmark datasets, in which CodedFedL speeds up the overall training time by up to 15× in comparison to the benchmark schemes.

The support of unmanned aerial vehicles, also known as drones, in cellular networks has become very important to enable a wide range of new applications for the next generation wireless systems. However, the cellular networks have been traditionally designed to serve terrestrial users, and thus are encountering many challenges to support drone wireless communication. Particularly, drones experience increased interference and channel fluctuation and consequently suffer more frequent handover, higher handover failure rate and ping-pong rate while in motion. In this paper, we propose enhanced mobility management for drones by exploiting their pre-configured flight path information. Our route-aware handover algorithm will instruct the base station to trigger the handover procedure to minimize handover failure and reduce unnecessary handover. We further provide a practical implementation where the network can make online decisions under realistic modeling assumptions. Based on 3GPP-compliant handover evaluation methodology, we demonstrate that our algorithm can effectively reduce the number of handover and handover failure by upto 32× and 24×, respectively, compared to the existing approach. This significantly reduces handover signalling overhead and service interruption time. The simulation results also show that our algorithm can completely eliminate ping-pong effect in certain cases.

Given that the accuracy of range-based positioning techniques generally increases with the number of available anchor nodes, it is important to secure more of these nodes. To this end, this paper studies an unsupervised learning technique to obtain the coordinates of unknown nodes that coexist with anchor nodes. As users use the location services in an area of interests, the proposed method automatically discovers unknown nodes and estimates their coordinates. In addition, this method learns an appropriate calibration curve to correct the distortion of raw distance measurements. As such, the positioning accuracy can be greatly improved using more anchor nodes and well-calibrated distance measurements. The performance of the proposed method was verified using commercial Wi-Fi devices in a practical indoor environment. The experiment results show that the coordinates of unknown nodes and the calibration curve are simultaneously determined without any ground truth data.

In wireless mobile edge computing platforms, such as those supported by vehicular networks, location specific machine learning models can be trained by distributing computations using resources available at the edge. The computational and communication resources at the wireless edge are heterogeneous and unreliable, which can lead to straggler effects that significantly slow down recursive learning tasks, such as gradient descent. In this paper we propose a coded computation framework, which utilizes statistical knowledge of resource heterogeneity to determine optimal encoding and load balancing of training data using Random Linear codes, while avoiding an explicit step for decoding gradients. Results show that the proposed coding framework speeds up the training time for linear regression models, by up to ten times, when compared with repetition coding schemes.

A typical wireless transceiver includes a radio frequency integrated circuit (RFIC) and a baseband modem (BBIC) which are connected through an input/output (I/O) interface. The wide-bandwidth and high-rate millimeter wave (mmWave) systems put a heavy burden on the power dissipation of the I/O interface of a transceiver. In this paper, a novel low power fully digital architecture with blind beam tracking and spatial compression (FDA-BTSC) is introduced to reduce the rate and power dissipation of the I/O interface. Spatial compression of the received signal is feasible due to the sparsity of mmWave channels. An efficient spatial compression is realized through codebook-based beamforming and fast blind beam tracking. Provided analysis and evaluations show that the proposed architecture is potentially as power efficient as existing analog and hybrid mmWave architectures. In addition, FDA-BTSC significantly drops the baseband processing complexity and power consumption level to the same order as hybrid beamforming, while it maintains the advantages of the fully digital beamforming in terms of low latency of the beam management and high efficiency of the digital beamforming.

We present a method for parallel dynamic cell selection and link scheduling in order to simultaneously activate a subset of non- interfering transmitter-receiver links to manage the interference in an ultra-dense network setting. We show how we can utilize a practical feedback method for periodic reporting of channel state information measured at the users back to the network to enable implementing our interference management scheme. Through simulation results, we demonstrate the superiority of our proposed interference management scheme over several benchmark schemes in terms of sum-rate and network coverage.

Dense deployments of millimeter-wave (mmWave) base stations (BSs) are being considered as the most feasible solution to meet the steadily growing data rate demands of mobile users. Accordingly, the achievable performance gains of mmWave-based dense networks in real deployments have to be studied carefully, since mmWave radio technology features specific transceiver, antenna, and propagation properties. In this paper, we contribute an accurate performance evaluation of single- versus dual-polarized MIMO systems operating over the mmWave channel in typical urban scenarios as well as address the impact of device- and network-centric parameters on the performance gains enabled by MIMO in dense to ultra-dense BS deployments. This study relies on our in-house ray-based modeler and takes into account the key mmWave system effects, such as multi-path propagation, utilization of dual-polarized antennas, and characteristic interference models. Our results show that the benefit of using mmWave- MIMO grows with increasing BS density, thus encouraging a further study of this technology especially for (ultra-)dense setups. We also demonstrate that non-coherent non-polarized diffuse scattering component may reduce the capacity gain of dual-polarized vs. single- polarized MIMO.

Generation and detection of millimeter-wave carrying orbital angular momentum (OAM) have been of growing interest. In this paper, we evaluate patch antenna arrays with different arrangements as OAM generators and receivers by simulation. We compare beam evolution processes and steering performance for circular and ring-antenna-array based OAM links. Mode purity of the generated OAM +1 beam fluctuates between 10% and 99% for ring antenna arrays with 10 cm diameters while it remains >99% for circular antenna arrays. Compared to a ring-antenna-array based link, the circular-antenna-array based link could have an ~10 dB lower power loss at the distance up to 0.5m. We also show that a 5cm diameter circular antenna array could steer an OAM +1 beam up to 80° with a mode purity degradation of <;1%, while ring antenna arrays have ~10% mode purity degradation. OAM spectrum analysis shows both the lattice shape and the boundary shape of an antenna array could cause power leakage to harmonic OAM orders. Such power leakages would increase as the designed OAM order or the lattice period d increases, while it would decrease as the array diameter D increases.

We propose a method for interference mitigation in an ultra-dense wireless network scenario in 5G, where a group of transmit points (TPs) intend to serve multiple user equipments (UEs) using the same wireless resource. The proposed UE scheduling subroutine may schedule a single UE or multiple UEs for each TP, where multiple UEs can be served via non-orthogonal multiple-access (NOMA). Afterwards, the link scheduling subroutine utilizes an extended form of the optimality conditions for treating interference as noise in single-user networks for the case where NOMA is also involved. This subroutine determines an activation/deactivation pattern of TPs while maintaining fairness among competing users and minimizing the level of interference among concurrent transmissions. We show that our proposed interference management scheme can improve over the benchmark schemes both in terms of sum-throughput and coverage, striking the right trade-off between these two performance metrics.

This paper reports an experimental investigation of using orthogonal frequency division multiplexing (OFDM) on orbital-angular momentum (OAM) channels when there is intersymbol interference (ISI) caused by multipath effects. The impulse response measurement indicates that due to the divergence of OAM beams, channels of larger OAM number are more affected by the ISI caused the reflections from surrounding objects. Channel performance of three different OAM numbers l = 0, +1 and +3 are studied. When a single QPSK channel is used, the more channel performance degradation in term of BER and EVM is observed for higher OAM channels. OFDM with 4 sub-carriers is used on the OAM channels to help reduce the ISI and improve the channel performance to some extent.

In this paper, the generation and steering of beams carrying orbital angular momentum utilizing a custom-designed circular antenna array has been demonstrated at 28 GHz. A steering angle as large as 30 degrees for an orbital angular momentum (OAM) beam has been achieved. The effect of number of antennas and the distance from antennas to the array center to the quality of beam generation and beam steering is investigated through both experiments and simulations. Our results indicate that: (1) As the steering angle increases, the mode purity of the generated OAM beams decreases; (2) Increasing the number of antennas improves the OAM mode purity; (3) For a fixed number of antennas, high mode purity is observed for lower order OAM modes; (4) Placing the antennas farther away from the array center allows for reduced divergence of the generate OAM beams.

This paper reports an experimental demonstration of a 32-Gbit/s wireless link using orbital angular momentum (OAM) and polarization multiplexing in a millimeter-wave regime at 60 GHz. Results of the analysis show that a higher carrier frequency reduces the propagation loss as well as the size of the transmitter and receiver, particularly for OAM channels with higher OAM values. Further, two different OAM channels (with l = +1 and l = +3) on each of the two polarizations are spatially multiplexed, and each channel carries 2-Gbaud signals with 16-QAM modulation. Spiral phase plates are used to generate 60-GHz OAM beams. The simulation results show that a higher carrier frequency plays a more significant role in reducing both the aperture size and the transmission loss for channels with higher OAM values. The bit error rates (BERs) of 4 channels are measured, and the raw BERs are found to be less than 3.8 × 10−3

We present a short-range experimental orbital-angular-momentum (OAM) multiplexing millimeter-wave communication system using patch antenna arrays. The dependence of the evolution of OAM beams on the number of array elements and array radius are analyzed. We also find phase delay deviation of 30 degrees leads to mode purity degrading to ∼1% and power deviation of 6 dB reduces the purity by <40%. An obstruction of size <10mm has not much influence on the evolution of OAM beams generated from antenna arrays with r = 8mm, which enables the stacking of multiple antenna arrays. We also use these patch antenna arrays to demonstrate a 60 GHz wireless communication link using two multiplexed OAM modes, each carrying a 500-Mbaud 16-QAM or 2-Gbaud QPSK signal. A channel crosstalk of less than −20 dB and bit-error-rates (BER) of less than 3.8 × 10−3 are achieved.

This article investigates novel adaptive self-interference cancellation solutions and the total integrated cancellation performance of a mobile single-antenna inband full-duplex transceiver. First, novel self-adaptive digital self-interference cancellation algorithms are described, with an emphasis on tracking of time-varying self-interference coupling channel in a mobile device as well as on structural ability to suppress also nonlinear self-interference with highly nonlinear mobile power amplifiers. This leads to an advanced self-adaptive nonlinear digital canceller which utilizes a novel orthogonalization procedure for nonlinear basis functions, together with low-cost LMS-based parameter learning. The achievable self-interference cancellation performance is then evaluated with actual RF measurements using mobile device scale RF components, in particular a highly nonlinear PA. The measurements also incorporate a novel self-adaptive RF cancellation circuit in order to realistically assess the total integrated cancellation performance. The reported results show that highly efficient self-interference cancellation can be achieved also in a mobile device, despite a heavily nonlinear PA and limited computing and hardware resources. The proposed cancellation solutions, when integrated together, show that 100 dB of self-interference can be cancelled using a 20 MHz LTE waveform, while the SI can be attenuated by over 110 dB with a narrower bandwidth of 1.4 MHz, all measured at 2.4 GHz ISM band. Furthermore, these results are achieved using a highly nonlinear transmitter power amplifier and fully adaptive canceller structures which can track a rapidly changing coupling channel in a mobile full-duplex device.

This paper reports on an experimental measurement and analysis of multipath-induced intra- and interchannel crosstalk effects in a mm-wave communications link using orbital angular momentum multiplexing at 28 GHz. The reflection is from an ideal reflector parallel to the propagation path. The intra-channel crosstalk effect is measured when a single OAM beam is transmitted, and inter-channel crosstalk effect is measured when 2 multiplexed OAM beams are transmitted. Both simulation and experimental results show that OAM channels with larger OAM number ℓ tend to have stronger intra-channel crosstalk because less power is received from the direct path and more power is received from the reflected path. This effect is caused by OAM beam divergence, as OAM beams with larger ℓ spread into a larger beam size and have less power in the beam center. For the same reason, OAM beams of larger ℓ lead to stronger inter-channel crosstalk with the other OAM channels.

We present the design and performance characterization of a thin metamaterial plate for generation of orbital angular momentum (OAM) modes of a millimeter-wave beam, which can carry independent data streams over the same physical medium. The plate has a thickness of 1.56 mm, and consists of 3.06 × 0.68 mm rectangular apertures with spatial variant orientations. It generates OAM beams l = +1 and l = +3 with mode purity larger than 77.5% over a bandwidth of 6 GHz (25-31 GHz). We then use these streams to experimentally demonstrate a 16-Gbit/s millimeter-wave wireless communications link using two multiplexed OAM modes, each carrying a 2-Gbaud 16-QAM signal. A channel crosstalk less than -20 dB over a bandwidth of 4 GHz (26-30 GHz) and biterror-rates (BER) less than 3.8 × 10-3are achieved.

This paper presents a novel RF circuit architecture for self-interference cancellation in inband full-duplex radio transceivers . The developed canceller is able to provide wideband cancellation with waveform bandwidths in the order of 100 MHz or beyond and contains also self-adaptive or self-healing features enabling automatic tracking of time-varying self-interference channel characteristics. In addition to architecture and operating principle descriptions, we also provide actual RF measurements at 2.4 GHz ISM band demonstrating the achievable cancellation levels with different bandwidths and when operating in different antenna configurations and under low-cost highly nonlinear power amplifier. In a very challenging example with a 100 MHz waveform bandwidth, around 41 dB total cancellation is obtained while the corresponding cancellation figure is close to 60 dB with the more conventional 20 MHz carrier bandwidth. Also, efficient tracking in time-varying reflection scenarios is demonstrated.

As fourth generation communications technology is already being deployed, research efforts are now being shifted to what comes beyond state-of-the-art wireless systems. Driven by the anticipated acceleration in mobile traffic demand, the wireless industry is specifically focused on improving capacity and coverage of current networks through aggressive reuse of the cellular spectrum. Together with deploying an increasingly dense overlay tier of smaller cells, mobile network operators are beginning to rely on unlicensed-band WLAN technologies to leverage additional spectrum and relieve congestion on their networks. Consequently, the emerging vision of heterogeneous networks exploits the potential of a diverse range of devices requiring connectivity at different scales to augment available system capacity and improve the user connectivity experience. In this paper, we seek to meet this important trend with our novel integrated methodology for assisted (managed) radio network selection capturing spatial randomness of converged cellular/WLAN deployments together with dynamic uplink traffic from their users. To this end, we employ tools coming from stochastic geometry to characterize performance of macro and pico cellular networks, as well as WLAN, mindful of user experience and targeting intelligent network selection/assignment. We complement our analysis with system-level simulations providing deeper insights into the behavior of future heterogeneous deployments.

Multi-radio heterogeneous networks (Het-Nets) are an important focus area for next generation cellular standards, with the 3GPP community actively developing WiFi/LTE interworking solutions for small-cell deployments. This paper explores coordinated usage of multiple radios (e.g., LTE and WiFi) to improve quality of service (QoS) in multi- radio heterogeneous networks. We focus on heterogeneous network deployments based on co- located WiFi-LTE small cells that allow for tighter multi-radio coordination. To evaluate QoS enhancements, we consider on-time throughput, a metric that captures the deliverable data rate for traffic with delay deadlines. A QoS-aware scheduling algorithm is designed to optimize on-time throughput. Cross-RAT coordination schemes are also explored to further enhance QoS. Through combining the QoS-aware scheduling algorithm and intelligent radio link assignment, we observe significant improvement in per user on-time throughput. Our results indicate that tightly coupled integrated LTE-WiFi small cell architectures can significantly increase the number of user achieving their targeted QoS.

We develop cognitive resource allocation scheme to mitigate co-tier and cross-tier interference in overlay femtocell networks. By exploiting statistical models for characterizing multitier interference, our scheme avoids prohibitive exchange of realtime interference statistics in the network. The proposed scheme is independently implemented at each femtocell and allocates resources distributedly in response to the probabilistic interference conditions in the network. This “self-organizing” framework can be useful to address interference management in dense, ad-hoc, and consumer-deployed femtocell networks. Simulation results show that the proposed scheme can improve the throughput of femtocell links while simultaneously reducing cross-tier interference.

Energy-efficient wireless communication is very important for battery-constrained mobile devices. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget because of RF power requirements for reliable transmission over long distances. Our previous work in this area focused on optimizing energy efficiency by maximizing the instantaneous bits-per-Joule metric through iterative approaches, which resulted in significant energy savings for uplink cellular OFDMA transmissions. In this paper, we develop energy efficient schemes with significantly lower complexity when compared to iterative approaches, by considering time-averaged bits-per-Joule metrics. We consider an uplink OFDMA system where multiple users communicate to a central scheduler over frequency-selective channels with high energy efficiency. The scheduler allocates the system bandwidth among all users to optimize energy efficiency across the whole network. Using time-averaged metrics, we derive energy optimal techniques in "closed forms" for per-user link adaptation and resource scheduling across users. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions obtained through exhaustive search.

Power optimization techniques are becoming increasingly important in wireless system design since battery technology has not kept up with the demand of mobile devices. They are also critical to interference management in wireless systems because interference usually results from both aggressive spectral reuse and high power transmission and severely limits system performance. In this paper, we develop an energy-efficient power optimization scheme for interference-limited wireless communications. We consider both circuit and transmission powers and focus on energy efficiency over throughput. We first investigate a non-cooperative game for energy-efficient power optimization in frequency-selective channels and reveal the conditions of the existence and uniqueness of the equilibrium for this game. Most importantly, we discover a sufficient condition for generic multi-channel power control to have a unique equilibrium in frequency-selective channels. Then we study the tradeoff between energy efficiency and spectral efficiency and show by simulation results that the proposed scheme improves both energy efficiency and spectral efficiency in an interference-limited multi-cell cellular network.

In order to meet the constantly increasing demand for ubiquitous, mobile access to the internet, next-generation mobile broadband communications systems based on OFDMA, such as IEEE 802.16 m, require a significant performance increase over previous generation systems, such as IEEE 802.16e-2005, particularly in cell-edge and average spectral efficiency. In this paper, we address the downlink adaptive frequency reuse (AFR) and multi-user MIMO (MU-MIMO) techniques which are considered to be the most promising candidates for meeting the requirements on cell-edge and average spectral efficiency of next-generation mobile broadband systems.

While the demand for battery capacity on mobile devices has grown with the increase in high-bandwidth multimedia rich applications, battery technology has not kept up with this demand. Therefore power optimization techniques are becoming increasingly important in wireless system design. Power optimization schemes are also important for interference management in wireless systems as interference resulting from aggressive spectral reuse and high power transmission severely limits system performance. Although power optimization plays a pivotal role in both interference management and energy utilization, little research addresses their joint interaction. In this paper, we develop energy-efficient power optimization schemes for interference-limited communications. Both circuit and transmit powers are considered and energy efficiency is emphasized over throughput. We note that the general power optimization problem in the presence of interference is intractable even when ideal user cooperation is assumed. We first study this problem for a simple two-user network with ideal user cooperation and then develop a practical non-cooperative power optimization scheme. Simulation results show that the proposed scheme improves not only energy efficiency but also spectral efficiency in an interference-limited cellular network.

Energy efficient communications in wireless communications is very important as mobile devices are battery- constrained. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget, due to the RF power requirements for reliable communications over long distances. Our previous work in this area demonstrated significant energy savings in uplink cellular OFDMA transmissions, with iterative approaches maximizing the instantaneous bits-per- Joule energy efficiency. In this paper, we use a time-averaged bits-per-Joule metric to develop low-complexity schemes. Specifically, we obtain closed-form solutions for energy-efficient link adaptation in frequency-selective channels. We also derive closed- form approaches for the maximum arithmetic and geometric mean energy-efficient schedulers. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions.

Severe cochannel interference in wireless cellular networks significantly affects users at cell edges. We propose a cost-effective cochannel interference avoidance (CIA) medium access control (MAC) scheme to improve network performance. For CIA-MAC, base stations judged as severe interferers transmit randomly and the transmission is controlled by wireless channel states to optimize the overall network performance while maintaining proportional fairness among users. Conditions for triggering CIA-MAC are derived and two simple trigger mechanisms are obtained. The CIA-MAC scheme requires low signaling overhead and only minor changes to the existing mobile systems. Simulation results show that the proposed scheme, CIAMAC, significantly outperforms traditional approaches through the avoidance of severe cochannel interference as well as the exploitation of multiuser diversity through cross-layer design.

This paper compares the system performance of transmit diversity schemes for use in interference-limited cellular systems. We focus on evaluating the performance of Alamouti space time block codes (STBC) and cyclic delay diversity (CDD) codes, which are being actively considered for adoption within the 3 GPP-long-term-evolution (LTE) and 802.16e WiMAX standards. While the performance of transmit diversity schemes has been extensively evaluated in noise-limited scenarios, their performance in co-channel interference (CCI) limited cellular systems has received limited attention so far. As cellular systems adopt frequency reuse of one, co-channel interference from other cells becomes a major limitation to system performance. We present system simulation results comparing the performance of transmit diversity schemes using matched filter reception for a multi-carrier OFDM-based cellular system. In particular, the performance of STBC and CDD schemes is compared with respect to the evolving third generation 3 GPP-LTE standard. Our comparison highlights the spatial as well as the multi-user diversity aspects of these schemes and considers a variety of scenarios that will require their use. Our results show that CDD can significantly improve the system spectral efficiency and cell-edge performance over STBC, when used in combination with frequency-dependent scheduling. For open loop transmission without scheduling, the relative diversity gains of STBC and CDD at link layer depend on the interference scenario considered, while the system performance of these schemes is very similar.

This paper investigates the effects of co-channel interference on spatial diversity techniques. By analyzing distributions of post-processing signal to noise plus interference ratio (SINR) after matched filtering, we capture the performance characteristics of spatial diversity techniques in an interference limited environment. Using intuition from the theoretical analysis of a single carrier system, the performance of spatial diversity techniques in an OFDMA system with co-channel interference is also characterized. Our analytical and simulation results show that space time block code (STBC) schemes are more sensitive to co-channel interference than other spatial diversity techniques so their performance gain in a noise-limited environment can be lost in an interference-limited environment.

This paper investigates the interaction between multiuser diversity and spatial diversity in an interference-limited environment based on post-receiver-processing signal-to-interference-plus-noise ratio (SINR) distributions. If opportunistic scheduling is employed, spatial diversity effects limit the achievable multiuser diversity gain. This paper quantifies the interaction by using order statistic theory and shows a spatial diversity technique with a larger SINR variance can be more effective under opportunistic scheduling. Through analysis and simulations, the authors show that the cyclic delay diversity technique gets the most benefit from the opportunistic scheduling among likely spatial diversity techniques and outperforms space time block coding (STBC), even though STBC is generally considered the most effective transmit diversity technique in a noise-limited environment.

The performance of error control based on forward error correction (FEC) for MPEG-2 video transmission in an indoor wireless ATM LAN is studied. A multipath fading model is used to investigate the effect of errors on video transport. Combined source and channel coding techniques that employ single layer and scalable MPEG-2 coding to combat channel errors are compared. Simulation results indicate that FEC-based error control in combination with 2-layer video coding techniques can lead to acceptable quality for indoor wireless ATM video.

The finite alphabet property of digital communication signals, along with oversampling techniques, enables the blind identification and equalization of an unknown FIR channel carrying a superposition of such signals, provided they have the same (known) period. Applied to multi-user wireless communications, the same framework allows the blind separation of multiple finite alphabet signals received at all arbitrary antenna arrays through an unknown multipath propagation environment with finite delay spread. An algorithm is proposed and tested on simulated data.

Using oversampling and the finite-alphabet property of digital communication signals, it is possible to blindly identify an FIR channel carrying a superposition of such signals, provided they have the same (known) period, and certain rank conditions on the data and channel matrices are satisfied. In particular, this technique allows separation of finite alphabet signals, removal of intersymbol interference, and synchronization of the signals. An algorithm is proposed and tested on simulated data.>

Proposes a novel approach for separating and estimating multiple co-channel digital signals using an antenna array. The spatial response of the array is unknown. The authors exploit the temporal structure of the digital signals to simultaneously determine the array response and the bit sequence for each signal. Uniqueness of the estimates is established for signals with BPSK modulation format. This new approach is applicable to an unknown array geometry and propagation environment, which is particularly useful in digital mobile communications. Simulation results demonstrate its promising performance.>