This work introduces ns-3-NTN[5], a new open-source framework for full stack simulation of 5G NR Non-Terrestrial Networks (NTNs) in ns-31. Initiated by [15], ns-3-NTN integrates the 5G-LENA NR stack [17], 3GPP NTN channel models [1, 19], and LEO mobility models [20], enabling system-level performance evaluation under realistic satellite mobility and time-varying channel conditions. To encourage further adoption, we demonstrate an initial set of system simulation use cases for single-beam regenerative and transparent 5G NR NTN architectures, quantifying the impact of NTN-specific RTT on scheduling, HARQ operation, fairness, and throughput performance.

This study evaluates the performance of Wi-Fi-based indoor localization utilizing Fine Timing Measurement (FTM) as specified in the IEEE 802.11az standard. Under line-of-sight (LOS) conditions with additive white Gaussian noise (AWGN), we quantitatively analyze the influence of key parameters on localization accuracy, including geometric dilution of precision (GDOP), the number of measurements per responding station (RSTA), receiver signal-to-noise ratio (SNR), and channel bandwidth. These effects are validated through simulations conducted in a three-dimensional office environment using the open-source ns-3 network simulator. Additionally, we investigate the impact of measurement time budgets and background data traffic on localization accuracy, as well as the effects of high-priority FTM sessions on network throughput.

As a groundbreaking feature in IEEE 802.11be, multi-link operation (MLO) is expected to support emerging applications that are strongly delay-sensitive. A key to the effective use of MLO for such cases rests on the optimal allocation of application traffic across multiple links. Our initial simulation experiments in ns-3 reveal that the proposed traffic allocation policies in prior art are significantly sub-optimal in terms of achievable delay performance of multi-link devices (MLDs), particularly in the presence of legacy single-link devices (SLDs). In this work, we first develop a new analytical model for the mean end-to-end (E2E) delay, delay jitter and worst-case percentile latency performance of MLD-SLD-coexisting Wi-Fi 7 networks (largely unexplored to date) with saturated and unsaturated SLD traffic. Subsequently, the optimal traffic allocation strategies for minimizing the mean E2E delay and delay jitter are obtained and validated by ns-3 simulation results. It is shown that with the optimal policy, MLDs can achieve significantly better mean E2E delay, delay jitter, worst-case latency and delay cumulative distribution function (CDF) compared to existing solutions.

Sidelink is a 3GPP-standardized technology that enables direct UE-to-UE communication. Initially designed for licensed 4G spectrum (Release 15), it expanded to 5G NR (Release 16, 17). However, due to the recent availability of large swaths of unlicensed spectrum (notably 6 GHz in U.S.), 3GPP has initiated studies to support sidelink operation in such unlicensed bands (denoted as SL-U). SL-U specifications ride on adaptation of 5G NR operation from licensed to unlicensed bands (NR-U). This paper provides a first analytical framework to quantify SL-U network performance in saturation conditions, for comparative evaluation to NR-U. A Markov chain model for NR-U is first presented, as a basis for necessary (significant) modifications needed to capture SL-U-specific features - the representation of gap states in the SL-U model to account for the restriction that SL-U transmissions only occur at SL slot boundaries. The resulting analysis highlights the differences and consequent (negative) impact of current 3GPP-defined SL-U channel access rulemaking; the analytical estimates are validated by results from a custom simulation of channel access. The primary takeaway is that the SL-U throughput under current 3GPP access rules suffers significantly relative to NR-U, and thus needs amelioration for successful marketplace adoption in the future.

IEEE 802.11be (Wi-Fi 7) introduces a new concept called multi-link operation (MLO), which allows multiple Wi-Fi interfaces in different bands (2.4, 5, and 6 GHz) to work together to increase network throughput, reduce latency, and improve spectrum reuse efficiency in dense overlapping networks. To make the most of MLO, this paper proposes a new data-driven resource allocation algorithm for the 11be network with the aid of an access point (AP) controller. To maximize network throughput, a network topology optimization problem is formulated for 11be network, which is solved by exploiting the totally unimodular property of the bipartite graph formed by the connection between AP and station (STA) in Wi-Fi networks. Subsequently, a proportional fairness algorithm is applied for radio link allocation, network throughput optimization considering the channel condition, and the fairness of the multi-link device (MLD) data rate. The performance of the proposed algorithm on two main MLO implementations -multi-link multi-radio (MLMR) with simultaneous transmission and reception (STR), and the interplay between multiple nodes employing them are evaluated through cross-layer (PHY-MAC) data rate simulation with PHY abstraction.

This paper considers spatial-domain detector design for mutual interference mitigation among automotive MIMO-FMCW radars. This detector design is based on our previously derived interference signal model that fully accounts for the time-frequency incoherence and the slow-time code incoherence between the victim and interfering radars. Compared with our previous spatial-domain detector in [1], the proposed detector further exploits the structural property of both transmit and receive steering vectors of the interference for stronger interference mitigation. Preliminary numerical results confirm the performance of our proposed detector and show advantages over baseline detectors.

Sidelink in cellular networks enables direct exchange of data packets between devices without the need for network infrastructure, resulting in various benefits, including communication in out-of-coverage areas and possible decrease in latency by a considerable extent. Thus, sidelink is a favorable choice for applications like public safety communications and Vehicle-to-Everything (V2X) communications. As 4G Long Term Evolution (LTE) advanced to 5G New Radio (NR) under the Third Generation Partnership Project (3GPP), several new features were introduced to sidelink, such as two-stage Sidelink Control Informations (SCIs), data and control multiplexing, and feedback-based Hybrid Automatic Repeat Request (HARQ) with a configurable maximum number of transmissions. To conduct extensive NR sidelink link-level evaluations, a comprehensive simulation platform is essential. In this paper, we introduce the first publicly accessible 5G NR Link-Level Simulator (LLS) that supports major 5G NR sidelink features and complies with the 3GPP standards. This MATLAB-based simulator allows for flexible control over various Physical Layer (PHY) configurations, facilitating customized simulations on algorithm development and performance evaluations. We discuss the simulator’s structure and the sidelink features implemented in detail and evaluate the 5G NR sidelink performance using the developed simulator. Our simulation results indicate that the Block Error Rate (BLER) curves are insensitive to error-prone 2nd-stage Sidelink Control Information (SCI2) and number of Resource Blocks (RBs) allocated; however, the sidelink communication range is sensitive to the deployment environment. We also highlight the need for a careful choice of numerology, device power class and HARQ configuration to balance performance metrics for a variety of services based on 5G NR sidelink deployment scenarios.

With the introduction of Orthogonal Frequency Division Multiple Access (OFDMA) in 802.11ax, the role of the Access Point (AP) in Wi-Fi networks changes significantly, thanks to the opportunity of implementing more complex scheduling logic to handle Downlink (DL) traffic flows and simultaneously act as coordinator of Multi User (MU) Uplink (UL) transmissions. In this context, it becomes necessary to develop reliable network analysis and simulation tools that allow for an in-depth investigation of the trade-offs involved in the usage of OFDMA, especially considering that the standard leaves much of the actual scheduling algorithmic details to vendor-specific implementation. In this work we present a series of results highlighting how several network settings have an impact on throughput and Head-of-Line Delay, in a network that employs multiple 802.11ax features such as OFDMA and the MU Enhanced Distributed Channel Access (EDCA) Parameter Set, while also containing legacy devices. The results are obtained via both the newly re-designed ns-3wifimodule and an original analytical framework, based on the well-established Bianchi 802.11 model.

Since the Third Generation Partnership Project (3GPP) specified 5G New Radio (NR) sidelink in Release 16, researchers have been expressing increasing interest in sidelink in various research areas, such as Proximity Services (ProSe) and Vehicle-to-Everything (V2X). It is essential to provide researchers with a comprehensive simulation platform that allows for extensive NR sidelink link-level evaluations. In this paper, we introduce the first publicly accessible 5G NR link-level simulator that supports sidelink. Our MATLAB-based simulator complies with the 3GPP 5G NR sidelink standards, and offers flexible control over various Physical Layer (PHY) configurations. It will facilitate researcher's exploration in NR sidelink with a friendly access to the key network parameters and great potential of customized simulations on algorithm developments and performance evaluations. This paper also provides several initial link-level simulation results on sidelink using the developed simulator.

Integrated access and backhaul (IAB) is a novel feature for extending the network coverage in 5G cellular networks, based on sharing/efficient allocation of owner’s spectrum traditionally reserved for access. However, since ultra-reliability and low latency (URLLC) requirements are a key component of 5G advanced services, provisioning such services present stringent challenges for IAB multi-hop network design. To fulfill the URLLC requirements in the IAB network, we propose a cross-layer design on routing and resource allocation under the current 3rd Generation Partnership Project (3GPP) 5G standards. We first formulate a routing problem for the IAB multi-hop network, which minimizes the latency while satisfying the reliability requirement. Subsequently, we present a reinforcement learning (RL) framework to solve the resource allocation and routing problem based on the local information of each agent (IAB node) in the environment. Afterward, we propose a novel entropy-based RL algorithm with federated learning (FL) mechanism to improve the overall performance as well as accelerate the convergence speed. Via the simulation, the proposed algorithm outperforms baseline algorithms from the latency and reliability perspective, respectively. Meanwhile, the convergence speed with the proposed algorithm also improves by using FL.

Network densification has led to a renewed emphasis on means to improveaggregate network throughputfor next-gen (High Efficiency) WLANs. The introduction of BSS color feature in support of enhanced spatial reuse sets IEEE 802.11ax apart from legacy WLAN. BSS color enables stations within a network to identify whether a transmission originates from an overlapped BSS and provides an option for mitigating the exposed node problem by allowing it to transmit (over the on-going OBSS transmission) albeit with reduced transmit power. As a result, distances between networks can be reduced, thereby improving the area spectral efficiency. To the best of our knowledge, this is the first work to develop an analytical model for IEEE 802.11ax spatial reuse that provides useful rules for optimizing network area throughput. We show that the spatial reuse gain is tightly linked to the interference range properties of each BSS in the network. Further, the analytical model predictions are validated and expanded via definitive ns-3 simulation results exploiting a recently concluded upgrade to 802.11 WLAN network stack (that implemented the necessary spatial reuse features).

With the rising utilization of radars on vehicles, interference among vehicular radars in dense traffic scenarios is an emerging problem awaiting innovative solutions. In this work, we consider incoherent FMCW radar interference cases where different FMCW radars use different chirp slopes. Our simulation shows that under the simplest spectrum access scheme - random frequency division multiplexing (RFDM), the false alarm caused by incoherent interference is a serious issue. We study the interference mitigation performance of three slow-time waveform randomization schemes: frequency hopping (FH), joint RFDM and phase coding (PC), and joint FH and PC. Our comparative study shows that not all slow-time waveform randomization schemes perform well under incoherent interference. FH even achieves worse false alarm performance than RFDM. Joint RFDM and PC achieve the best trade-off between the probability of false alarm and the probability of target detection.

Packet-level wireless (802.11ax or 5G) network simulators face escalating system dimensionality resulting from dense deployment scenarios supporting wideband, Multi-Input Multi-Output (MIMO), Multi-User (MU) transmission. Managing the resulting network simulation complexity and achieving practical runtimes require continuing enhancements to physical (PHY) layer abstractions. This work improves the state-of-the-art PHY layer abstractions via a new computational workflow that maps extensive offline link simulation results for OFDM/OFDMA MIMO/MU-MIMO system performance over frequency-selective fading channels into Packet Error Ratio (PER) for network simulations. The proposed method is shown to require modest additional storage and the runtime is insensitive to the increase in PHY layer dimensionality. We describe the principles of this new method and provide details about its implementation, performance, and validation.

5G New Radio (NR) is envisioned to efficiently support both enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC). Due to the severe constraint of URLLC traffic, the time resources used by eMBB are further divided into mini-slots. From the media access control (MAC) layer scheduling perspective, the resource allocation occurs on different timescales, and URLLC traffic is pre-emptively overlapped at the mini-slot timescale to obtain the strict requirements of URLLC (achieve 99.999% reliability within 1 ms latency). In this article, we analyze the multiplexing of eMBB and URLLC traffic in 5G downlink transmission, with the dual objectives of maximizing eMBB utility like proportional fairness for eMBB users while satisfying URLLC constraints. We formulate the resource allocation problem in each mini-slot as the integer programming (IP) problem with two solutions: 1) convex relaxation; 2) greedy algorithm. The simulation results show that our algorithms have a higher utility of eMBB users while satisfying the URLLC users' latency and reliability requirements than using basic round robin. The performance comparison between the two algorithms is extensively studied, and the choice of two algorithms in practice can be decided by the trade-off analysis investigated in this article.

A novel bidirectional computation task model has emerged as an important use case of 5G. For example, interactive AR/VR gaming service needs to render the live scene by jointly computing user features such as 3D positions and video data generated from the Internet. In this article, we consider the bidirectional computation task model, where each task is served via three mechanisms, i.e., local computing with local caching, local computing without local caching, and computing at the mobile edge computing server. To minimize the average bandwidth, we formulate the joint caching and computing optimization problem under the latency, cache size and average power constraints. In the homogeneous scenario, we derive the optimal policy and analytical expression for the minimum bandwidth. In the heterogeneous scenario, to reduce the computation complexity of the NP-hard problem, we relax some constraints of the original problem and propose a Lagrangian relaxation (LR) suboptimal solution, which may be infeasible. We then reformulate the original problem as an auxiliary problem based on the LR solution and solve this via Concave-Convex Procedure (CCCP), which outputs feasible local optimal solution. Simulation has shown that LR-based algorithms outperform the baselines including greedy and CCCP algorithms in the bandwidth performance and time efficiency.

IEEE 802.11ax partitions a regular 20MHz channel into smaller sub-channels called resource units to support simultaneous multiuser operation using orthogonal frequency division multiple access (OFDMA). Uplink OFDMA random access (UORA) in IEEE 802.11ax allows stations to transmit via a scheduled random access mechanism. UORA is initiated via a trigger frame which aside from serving as a synchronization mechanism, also informs stations which resource units are allowed for random access. Using the trigger frame information, the stations engage in an OFDMA backoff process to win access to a resource unit. Similar to slotted ALOHA, the maximum normalized throughput of UORA is only 37 percent due to high probability of collisions at high loads. To reduce collisions, we equip UORA with carrier sensing capability resulting in anewuplink hybrid UORA (H-UORA) OFDMA access mechanism. Unlike other multi-carrier CSMA methods previously proposed in literature, H-UORA is an easily implementable modification to current 802.11ax WLANs. We show that H-UORA can achieve a normalized throughput of at least 80 percent (which increases further depending on the buffering capabilities of the access point) using various numerical analysis and simulations.

We investigate the coexistence of an age optimizing network (AON) and a throughput optimizing network (TON) that share a common spectrum band. We consider two modes of long run coexistence: (a) networks compete with each other for spectrum access, causing them to interfere and (b) networks cooperate to achieve non-interfering access. To model competition, we define a non-cooperative stage game parameterized by the average age of the AON at the beginning of the stage, derive its mixed strategy Nash equilibrium (MSNE), and analyze the evolution of age and throughput over an infinitely repeated game in which each network plays the MSNE at every stage. Cooperation uses a coordination device that performs a coin toss during each stage to select the network that must access the medium. Networks use the grim trigger punishment strategy, reverting to playing the MSNE every stage forever if the other disobeys the device. We determine if there exists a subgame perfect equilibrium, i.e., the networks obey the device forever as they find cooperation beneficial. We show that networks choose to cooperate only when they consist of a sufficiently small number of nodes, otherwise they prefer to disobey the device and compete.

Channel bonding in IEEE 802.11 wireless LANs is a technique whereby adjacent 20MHz channels are `bonded' to create a wider bandwidth channel that supports higher data rate transmissions. Although rate improvements due to channel bonding has been shown in sparse wireless LAN environments, its effectiveness in dense scenarios requires further exploration due to increased sensitivity to interference from overlapping co-channel basic service sets. With the newly finalized 802.11ax standard supporting enhanced spatial reuse feature, its impact on the expected gains from channel bonding needs careful analysis. In this work, we propose a new analytical framework that accurately models the performance of channel bonding as a function of both PHY and MAC parameters for a dense network scenario. A new channel bonding algorithm that is robust to overlapped co-channel interference is described, i.e. it preserves channel bonding gains by intelligently choosing the channel bonding bandwidth based on network conditions and parameters that are readily available to all stations, critically the modulation scheme chosen for packet transmission. The predicted gains of the proposed algorithm are verified via comprehensive simulations conducted with the open source network simulator ns-3.

With the increasing density of vehicular radars on the road, interference among vehicular radars is becoming an important problem. In this work, we consider a frequency modulated continuous wave (FMCW) radar multiple access network and develop mutual interference models for analyzing target-ghost classification performance. We next define a cross-layer performance metric called multiple access capacity that is analyzed under a simple random access scheme (un-slotted ALOHA) to obtain system design insights.

Unmanned Aerial Vehicles (UAVs) or drones have found a tremendous range of civilian and commercial applications such as precise agriculture, environmental conservation, and search and rescue missions. In this paper, we re-visit the positioning of a low altitude UAV functioning as a relay node to provide connectivity and communication services to ground users who are out of coverage. A new altitude dependant Rician distribution for the air-to-ground channel - derived from propagation physics - is used and its impact on the optimum altitude for network coverage explored via numerical results.

With the advent of the modern mobile traffic, e.g., online gaming, augmented reality delivery and etc., a novel bidirectional computation task model where the input data of each task consists of two parts, one generated at the mobile device in real-time and the other originated from the Internet proactively, is emerging as an important use case of 5G. In this paper, for ease of analytical analysis, we consider the homogeneous bidirectional computation task model in a mobile edge network which consists of one mobile edge computing (MEC) server and one mobile device, both enabled with computing and caching capabilities. Each task can be served via three mechanisms, i.e., local computing with local caching, local computing without local caching and computing at the MEC server. To minimize the average bandwidth, we formulate the joint caching and computing optimization problem under the latency, cache size and average power constraints. We derive the closed-form expressions for the optimal policy and the minimum bandwidth. The tradeoff among communications, computing and caching is illustrated both analytically and numerically, which provides insightful guideline for the network designers.

Carrier sensing multiple access/collision avoidance (CSMA/CA) is the backbone MAC protocol for IEEE 802.11 networks. However, tuning the binary exponential back-off (BEB) mechanism of CSMA/CA in user-dense scenarios so as to maximize aggregate throughput still remains a practically essential and challenging problem. In this paper, we propose a new and enhanced multiple access mechanism based on the application of deep reinforcement learning (DRL) and Federated learning (FL). A new Monte Carlo (MC) reward updating method for DRL training is proposed and the access history of each station is used to derive a DRL-based MAC protocol that improves the network throughput vis-a-vis the traditional distributed coordination function (DCF). Further, federated learning (FL) is applied to achieve fairness among users. The simulation results showcase that the proposed federated reinforcement multiple access (FRMA) performs better than basic DCF by 20% and DCF with request-to-send/clear-to-send (RTS/CTS) by 5% while guaranteeing the fairness in user-dense scenarios.

LTE Licensed Assisted Access (LTE-LAA) is a promising solution for harmonious coexistence with WiFi in unlicensed spectrum. Although LTE-LAA employs a listen-before-talk approach similar to the distributed coordination function in IEEE 802.11, it uses different parameters and varying transmission durations. As a result, achieving fair coexistence between LTE-LAA and WiFi (by any definition) remains an open question, which in a pragmatic framework, devolves to: how LTE-LAA should select its parameters. To address this issue, a multi-group model is proposed for LTE-LAA and WiFi coexistence, as a function of respective initial backoff window sizes, sensing durations, maximum backoff stages, retry limits and transmission opportunities. The network steady-state point in saturated conditions is obtained, based on which the node airtime and total network airtime are derived as functions of system parameters of LTE-LAA and WiFi networks. The analysis shows that LTE-LAA can maintain proportional fairness with WiFi by either tuning its initial backoff window size or sensing duration. In particular, the optimal initial backoff window size and number of sensing slots of LTE-LAA are both derived and verified by simulation. The significance of our analysis is two-fold: a) it exposes the result that the current standard-proposed parameter settings will not generically achieve fairness and thereafter b) suggests optimal settings whereby LTE-LAA and WiFi nodes can achieve equal per-node airtime. It is further revealed that the initial backoff window size tuning of LTE-LAA could be a preferable option for achieving fairness between LTE-LAA and WiFi in practical scenarios as it requires less system information and achieves better precision.

The performance of the Long Term Evolution (LTE) Device-to-Device (D2D) direct discovery process in out-of-coverage scenarios (Mode 2) is examined as a function of the predefined pool of time- frequency resources. Individual discovery periods are modeled as an ALOHA like protocol with Medium Access Control (MAC) layer collisions and either a half-duplex or a suggested Frequency Division Duplex (FDD) User Equipment (UE), the performance of which is compared. A simulation framework is described using the open source network simulator NS-3 and then performance of the discovery process evaluated as a function of the size of the resource pool and UE density. We provide a formulation for the number of discoveries made in one period and propose a heuristic for the choice of resource pool size based on the number of UE in discovery.

LTE-U (LTE-Unlicensed) is designed to coexist with Wi-Fi in the unlicensed band by balancing its duty cycle according to the number of coexisting Wi-Fi access points (APs) it detects. For example, a LTE-U base-station (BS) will reduce its duty cycle from 50% to 33% when it senses an increase in the number of co-channel Wi-Fi basic service sets (BSSs) from one to two. But the problem of detecting how many WiFi BSS' are operating on the channel in real-time, without decoding the Wi-Fi header, still remains. In this paper, we present a novel algorithm that solves the problem by using an autocorrelation (AC) function on the Wi-Fi preamble and setting appropriate detection thresholds to infer the number of Wi-Fi BSSs operating on the channel. Performing auto-correlation on the Wi-Fi preamble is a much simpler operation than decoding the entire Wi-Fi packet, which is what would be needed if one were to decode the MAC header to identify the BSS. We implement and experimentally validate the proposed AC detector and demonstrate that there is a differentiable pattern of AC events between one and two Wi-Fi APs. From the collected AC events, we determine a suitable threshold for a reliable detection of Wi-Fi APs. We show that using an AC threshold of NE= 0.8, we can achieve a probability of detection (PD) of 0.9 with a probability of false alarm (PFA) of less than 0.02. Finally, we demonstrate that the performance of the proposed AC detector is superior in terms of PDand PFA compared with the energy detector (ED).

In this paper, we develop an algorithm, based only on energy detection, to detect the number of Wi-Fi basic service sets (BSSs) operating on the same channel. Such an algorithm can be used by a LTE-U base station (BS) to scale back its duty cycle when coexisting with Wi-Fi on the same channel. According to the LTE-U specification, a LTE-U BS scales back its duty cycle from 50% to 33% when it senses that the number of co-channel Wi-Fi BSSs has increased from one to two. There are two ways that this detection can be done: (a) decoding based, where the LTE-U BS decodes the Wi-Fi packet header to determine the unique Wi-Fi basic service set identification (BSSID) and (b) energy based, where only received energy levels are used to determine the number of Wi-Fi BSSs. The former approach requires an LTE-U BS to implement a Wi-Fi decoder and hence increases complexity, whereas the latter is easier to implement, requiring only an energy detector and appropriate detection thresholds to distinguish between one and two Wi-Fi APs. We analyze the latter approach and experimentally verify the feasibility of an energy detector to reliably distinguish between one and two Wi-Fi APs. In order to do so, we first experimentally determine appropriate detection thresholds using comprehensive measurements in realistic environments, both line-of-sight (LOS) and non-LOS (NLOS). These thresholds are then used to perform hypothesis based detection to devise an efficient algorithm that predicts presence of one or two Wi-Fi BSSs. The performance of the proposed algorithm is evaluated, both theoretically and experimentally, by utilizing two metrics (a) probability of detection ($P_D$) and (b) probability of false alarm ($P_{FA}$). We show that using a threshold of -42 dBm delivers greater than 80% $P_D$ and less the 5% $P_{FA}$ which we verify both theoretically and experimentally. Hence energy based detection is a low-complexity means of determining number of Wi-Fi BSSs to help LTE-U scale back its duty cycle appropriately.

In this paper we address the issue of association fairness when Wi-Fi and LTE unlicensed (LTE-U) coexist on the same channel in the unlicensed 5 GHz band. Since beacon transmission is the first step in starting the association process in Wi-Fi, we define association fairness as how fair LTE-U is in allowing Wi-Fi to start transmitting beacons on a channel that it occupies with a very large duty cycle. According to the LTE-U specification, if a LTE-U base station determines that a channel is vacant, it can transmit for up to 20 ms and turn OFF for only 1 ms, resulting in a duty cycle of 95%. In an area with heavy spectrum usage, there will be cases when a Wi-Fi access point wishes to share the same channel, as it does today with Wi-Fi. We study, both theoretically and experimentally, the effect that such a large LTE-U duty cycle can have on the association process, specifically Wi-Fi beacon transmission and reception. We demonstrate via an experimental set-up using National Instrument (NI) USRPs that a significant percentage of Wi-Fi beacons will either not be transmitted in a timely fashion or will not be received at the LTE-U BS thus making it difficult for the LTE-U BS to adapt its duty cycle in response to the Wi-Fi usage. Our experimental results corroborate our theoretical analysis. We compare the results with Wi-Fi/Wi-Fi coexistence and demonstrate that LTE-U/Wi-Fi coexistence is not fair when it comes to initial association since there is a much larger percentage of beacon errors in the latter case. Hence, the results in the paper indicate that in order to maintain association fairness, a LTE-U BS should not transmit at such high duty cycles, even if it deems the channel to be vacant.

Compute-and-forward (C&F) recently finds new applications in random-access networks focusing on the single access point (AP) scenario. In this paper, we extend the use of C&F from the single AP scenario to the multi-AP scenario. To achieve this, we identify two major challenges and propose two novel solutions. First, we introduce an AP cooperation problem and develop an efficient distributed algorithm. Second, we introduce a joint channel estimation and active user recovery problem and propose a solution based on spare recovery techniques. In addition, we provide accurate throughput and delay expressions for C&F-based carrier-sense multiple access (CSMA) protocols. These expressions, together with our trace-driven simulations, demonstrate the significant advantages of C&F-based CSMA over conventional CSMA in the multi-AP scenario.

Coded caching has emerged as a promising component of solutions to the exponential growth in network traffic. Previous approaches to network coding are all based on (simple) XOR coding, which is appropriate when links have the same rate. However, in typical wireless networks, different users experience different link rates. Thus, XOR coding is sub-optimal and cannot achieve full broadcast gain. In this paper, we consider the coded caching design for wireless networks with unequal link rates. More specifically, the backhaul networks of LTE-A or 5G system are considered, in which the link rates between the macroBS and microBSs are different. We leverage a new network coding scheme nested coded modulation (NCM) in the delivery phase and develop a novel file partition scheme for the placement phase based on unequal cache size allocation. This scheme adapts to unequal link rates for increasing broadcast gains. The achievable transmission time and the information-theoretic lower bound are derived; we show that transmission time of the NCM-based coded caching can achieve a constant gap to the lower bound. Moreover, the NCM-based coded caching can achieve significant performance improvement over the XOR-based coded caching; the example with normalized link rates from 1 to 6 achieves up to 250% throughput improvement. Numerical results also show that the NCM-based coded caching can well utilize the unequal link rates, which cannot be achieved by the XOR-based coded caching.

This paper applies fundamental market-based approaches to the problem of (wireless) spectrum sharing between a licensed primary user (PU) and an unlicensed secondary user (SU). We consider both orthogonal and non-orthogonal modes of dynamic spectrum access (DSA), and explore rates and profits at market equilibrium. Our analytical formulation is distinct from prior art: we assume that 1) PU increases its transmit power (within bounds) to avoid any rate loss from DSA and 2) the spectrum owner provides compensation to exactly offset PU's increased power costs, leaving PU's overall economic well-being unaffected by DSA. This allows quantification of the marginal costs for various DSA schemes for fair comparison and insights into corresponding market behavior. Our analysis suggests that non-orthogonal DSA is more profitable when 1) spectrum owners face low competition; 2) SU is very sensitive to power consumption but not very sensitive to data rates (low or moderate rate applications); and 3) channel conditions imply low mutual interference between PU and SU; otherwise, orthogonal DSA is more profitable. Market competition has a very large impact on profits and rates under non-orthogonal DSA but not for orthogonal DSA. Finally, we explore a novel hybrid approach where some portion of the licensed bandwidth is reserved for PU's exclusive use and non-orthogonal DSA is permitted over the rest, we determine bounds on how much bandwidth should be reserved for PU in such cases.

The paradigm of shared spectrum allows secondary devices to opportunistically access spectrum bands underutilized by primary owners. Recently, the FCC has targeted the sharing of the 3.5 GHz (3550-3700 MHz) federal spectrum with commercial systems such as small cells. The rules require a spectrum access system (SAS) to accommodate three service tiers: 1) incumbent access; 2) priority access (PA); and 3) generalized authorized access (GAA). In this paper, we study the SAS-assisted dynamic channel assignment (CA) for PA and GAA tiers. We introduce the node-channel-pair conflict graph to capture pairwise interference, channel and geographic contiguity constraints, spatially varying channel availability, and coexistence awareness. The proposed graph representation allows us to formulate PA CA and GAA CA with binary conflicts as max-cardinality and max-reward CA, respectively. Approximate solutions can be found by a heuristic-based algorithm that searches for the maximum weighted independent set. We further formulate GAA CA with non-binary conflicts as max-utility CA. We show that the utility function is submodular, and the problem is an instance of matroid-constrained submodular maximization. A local-search-based polynomial-time algorithm is proposed which provides a provable performance guarantee. Extensive simulations using a real-world Wi-Fi hotspot location data set are performed to evaluate the proposed algorithms. Our results have demonstrated the advantages of the proposed graph representation and improved performance of the proposed algorithms over the baseline algorithms.

In this paper, a centralized coded caching scheme is developed for wireless backhaul networks with heterogeneous channel conditions, i.e., the wireless channels between microBSs and a macroBS have different link rates and packet loss rates. To address these heterogeneous channel conditions, a joint random linear network coding and nested coded modulation (RLNCNCM) encoding scheme is designed for the delivery phase. Based on RLNC-NCM encoding, broadcast opportunities can be fully utilized for each coded subfile transmission. To support RLNC-NCM transmission, unequal file partition and cache size allocation are conducted in the placement phase. It is shown that a microBS with weaker channel condition needs to be allocated with more cache size. The theoretical achievable transmission time of the RLNC-NCM coded caching scheme is also derived. Moreover, numerical results show that the coded caching scheme developed in this paper significantly reduces the transmission time as compared to the existing schemes.

Coexistence of Wi-Fi and LTE Unlicensed (LTE-U) in shared or unlicensed bands has drawn growing attention from both academia and industry. An important consideration is fairness between Wi-Fi and duty cycled LTE-U, which is often defined in terms of channel access time, as adopted by the LTE-U Forum. Despite many studies on duty cycle adaptation design for fair sharing, one crucial fact has often been neglected: LTE-U systems unilaterally control LTE-U duty cycles; hence, as selfinterested users, they have incentives to misbehave, e.g., transmitting with a larger duty cycle that exceeds a given limit, so as to gain a greater share in channel access time and throughput. In this paper, we propose a scheme that allows the spectrum manager managing the shared bands to estimate the duty cycle of a target LTE-U cell based on PHY layer observations from a nearby Wi-Fi AP, without interrupting normal Wi-Fi operations. We further propose a thresholding scheme to detect duty cycling misbehavior (i.e., determining if the duty cycle exceeds the assigned limit), and analyze its performance in terms of detection and false alarm probabilities. The proposed schemes are implemented in ns3 and evaluated with extensive simulations. Our results show that the proposed scheme provides an estimate within ± 1% of the true duty cycle, and detects misbehavior with a duty cycle 2.8% higher than the limit with a detection probability of at least 95%, while keeping the false alarm probability less than or equal to 1%.

The problem of carrier sense multiple access (CSMA) with multi-packet reception (MPR) is studied. Most prior work has focused on the homogeneous case, where all the mobile users are assumed to have identical packet arrival rates and transmission probabilities. The inhomogeneous case remains largely open in the literature. In this paper, we make a first step toward this open problem by deriving throughput and delay expressions for inhomogeneous CSMA, with a particular focus on a family of MPR models. This family of MPR models, which allows us to overcome several challenges associated with conventional analysis, is general enough to include a number of interesting MPR techniques-such as successive interference cancellation, compute-and-forward (C&F), and successive C&F (SCF)-as special cases. Based on these throughput and delay expressions, we provide theoretical guidelines for the network design to meet quality-of-service requirements and to achieve global stability; we also evaluate the performances of various MPR techniques, highlighting the clear advantages offered by SCF.

White Space (WS) Networking crucially relies on the active monitoring of spatio-temporal spectrum usage (to identify WS opportunities). To achieve this, one way is to gather spectrum data via wide-area sensor deployment and construct better Radio Environment Maps (REMs) with spatial models such as Kriging and Gaussian Process (GP). An economically viable alternative is via incentivized crowdsourcing, i.e., outsourcing sensing tasks to mobile users who have sensorized high-end client devices like tablets or smartphones, and providing proper incentives to compensate for users' sensing costs. In crowdsourced REM, features that impact REM performance and economic cost include user locations and the heterogeneity of user devices, which impact data quality and sensing costs. In this work, we emphasize the use of a hardware noise term in the GP model to account for data quality, and adopt mutual information to quantify sampling performance; we further design a pricing mechanism that allows the platform to maximize its expected utility at each stage and send optimal price offers to users sequentially, with joint consideration of sampling value, data quality and cost. We conduct simulations to evaluate the performance. Simulation results show that our mechanism outperforms two baseline mechanisms, and benefits from more users and less hardware noise (i.e., better data quality).

White-Fi networks are CSMA/CA networks that are deployed in TV white spaces. In outdoor deployments, nodes in such networks can have a communication range of several kilometers. As a result, nodes in range have heterogeneous channel gains from the TV transmitters. Also, they have heterogeneous channel gains to TV receivers. While the nodes in the network may be configured as an ad hoc network of peers or in infrastructure (access point based) mode, they use the 802.11 distributed control function (DCF) to gain access to the medium. We investigate optimization of the DCF throughput in such a White-Fi network when there are restrictions on the aggregate interference (specifically, we consider its expectation and maximum) that it can create at TV receivers. To gain insights into the interplay between the TV networks and the White-Fi network, we allow nodes in the White-Fi network to choose their payload rates, access probabilities, overhead transmission rates, and channels. The resulting optimization problem is non-convex. Our proposed solution methodology obtains large gains (about 200% for 50 nodes) in throughput over a baseline that respects restrictions on aggregate interference but assigns the same power and probability of medium access, across available channels, to all nodes in the network.

Devices like smart phones come with 3G/4G and WiFi radios, which creates possibilities of heterogeneous network access. We investigate scenarios where Internet access to a device is available only via the cellular network. However, not every user may connect directly to it. Users in the network may be split into hotspots and clients. Hotspots are the users that connect directly to the cellular network and may provide connectivity to the internet to other users by allowing them to connect to their WiFi interface. Clients connect to the cellular network only via hotspots. The optimization problem is to find the split of hotspots and clients, and the association between clients and hotspots, that maximizes the sum of the link rates of users. Importantly, the users must get at least the link rate they get when all are directly connected to the cellular network. In this paper, we formulate the optimization problem. We provide insights into the interplay of WiFi connectivity amongst users, their link rates to the cell tower, and the split that maximizes sum rate. We propose a novel heuristic approach to split the network. Median gains of 1.5× are observed over networks of up to 40 nodes.

This paper investigates the impact of radar interference on LTE by directly injecting narrow-band radar waveforms into a state of the art LTE down-link simulator. We show detailed results demonstrating the impact of interference on various parts of LTE signaling including reference symbols. Then we show how the presence of radar interference causes errors in the noise and interference estimates, impacts decoding in the LTE soft decoder, and ultimately leads to erroneously received Sub-frames. We propose a mechanism to combat such interference and improve LTE throughput in the presence of narrow-band radar using selective erasures. We simulate the proposed scheme and show that it is extremely effective in mitigating narrow-band interference and realizing the throughput expected from LTE.

The benefit of applying compute-and-forward (C&F) to slotted ALOHA (S-ALOHA) systems is studied. A Markov chain model is introduced, and an approximate stability region is given. It is shown that the approximate region is asymptotically exact as the number of users tends to infinity. It is also shown that the approximate region is very accurate even for systems with a small number of users. Further, based on the approximate region, simple expressions for the throughput and delay performance of S-ALOHA with C&F are derived, demonstrating the significant advantages offered by C&F.

In this paper, we study the relation between network capacity and the density of micro base stations in heterogeneous networks (HetNets) scenario consisting of macro base station (MaBS) and micro base station (MiBS) tiers. First, the distribution of the distance between a typical user and its serving base station (BS) is derived in a stochastic geometry model. Assuming users access the BS with the strongest received signal, we obtain the probability of users' association with the MiBS tier as a function of MiBS density. Then the impact of BS density on the interference inside the MiBS tier is also achieved in closed form. Finally, we derive the closed form solution of the network capacity as a function of BS density. We find that although there are more available channels with higher MiBS density, the rate of each channel is degraded because of stronger interference. Therefore the problem of maximizing network capacity with respect to MiBS density is formulated and the optimal MiBS density is obtained. Simulations are provided to verify the correctness of our analysis. One interesting finding is that network capacity doesn't increase monotonously with BS density. Thus deploying more MiBS may not always be a good choice1.

IEEE 802.11 WLAN (Wireless or WiFi LAN) clients discover neighboring APs (Access Points) by active or passive scanning. Such an active scan of WLAN injects probe frames in the network. Network conditions like packet losses, roaming, etc. result in increased active scanning and hence, an excessive increase of the probe traffic. Of the several causes inherent to WLANs like interference, we find an excessive probe traffic also has a potential of hampering goodput of a WiFi network. We confirm this behavior in a controlled home environment as well as in an uncontrolled enterprise environment. Our analysis of 36 hours of wireless traffic collected over a period of 5 months with approximately 45 million wireless frames reveals that goodput of a WLAN drops exponentially with increase in the probe traffic. Therefore, realtime detection of increase in probe traffic and knowledge of a threshold for acceptable probing is crucial for WLAN's performance. In this paper, we formulate a metric to measure the increase in probe traffic in realtime and evaluate its functioning empirically. The metric not only reflects increase in probe traffic correctly, it is even simple enough to allow its realtime measurement.

The primary challenge in heterogeneous cellular networks is mitigating intercell interference, particularly in dense deployments of residential femtocells. Traditionally, interference in wide-area cellular networks has been studied from a multicell resource-allocation perspective, where radio resources, e.g., power and bandwidth, in each cell are centrally managed to reduce interference. This approach generally assumes a fully loaded network (i.e., many simultaneous active users in a cell) where the system performance is insensitive to the activity of a single user. This assumption is not suitable for femtocells, which are designed to serve very few users and thus lack the presumed traffic aggregation. In this paper, we quantify the impact of the user activity factor by comparing the performance of centralized resource-allocation schemes represented by a highly idealized power control protocol to that of a simple random access protocol. Our analysis shows that, with a high probability, a simple un-optimized random access protocol would perform much better than a fair optimized power-controlled network in most of the unsaturated traffic scenarios. If the network is saturated, then a fixed orthogonal partitioning of the channel bandwidth among femtocells would be the best strategy to handle the interference. This result highlights the importance of modeling the random user activities and traffic patterns in the design and analysis of femtocell interference mitigation solutions.

An efficient random access protocol utilizing the frequency diversity of OFDMA is proposed for mitigating femtocell interference in a decentralized cellular network. The proposed OFDM reservation random access (OFDM-RR) protocol builds upon a generalized version of the frequency-domain backoff scheme, which was originally proposed for WiFi networks. In this protocol, each node chooses one of K subchannels randomly and transmits a short reservation request on the corresponding subchannel. At the end of the slot, the node whose subchannel index is the highest wins the contention and immediately transmits on the full channel. A tie on the highest index is treated as a collision and is resolved by repeating the process with only those nodes involved in the collision. The throughput of this protocol is derived and compared with that of the classic reservation Aloha (R-Aloha) with the same total channel bandwidth. Although channelization increases the transmission time of the reservation packet in OFDM-RR (due to the smaller subchannel bandwidth), the collision resolution mechanism, which reduces the collision rate sharply, helps improve the throughput, particularly in the high-load region. For example, while R-Aloha almost collapses (near zero throughput) at an average load of ten requests/slot, the proposed protocol can provide a throughput of more than 55% at the same load using only two subchannels.

The so-called “TV white spaces” (TVWS)-representing unused TV channels in any given location as the result of the transition to digital broadcasting-is designated for unlicensed use [1], [2], [3] by the US Federal Communications Commission (FCC). This presents significant new opportunities within the context of emerging 4G networks for developing new wireless access technologies that meet the goals of the US National Broadband Plan [4] (notably true broadband access for an increasing fraction of the population). There are multiple challenges in realizing this goal; the most fundamental being the fact that the available WS capacity is currently not accurately known, since it depends on a multiplicity of factors-including system parameters of existing incumbents (broadcasters), propagation characteristics of local terrain as well as FCC rules. In this paper, we explore the capacity of white space networks by developing a detailed model that includes all the major variables, and is cognizant of FCC regulations that provide constraints on incumbent protection. Real terrain information and propagation models for the primary broadcaster and adjacent channel interference from TV transmitters are included to estimate their impact on achievable WS capacity. The model is later used to explore various trade-offs between network capacity and system parameters and suggests possible amendments to FCC's incumbent protection rules in the favor of furthering white space capacity.

The sixteen articles in this special section explore advances in communication technologies that have the potential for improving energy efficiency and realizing the smart grid vision. The articles tackle important challenges with respect to smart grid communications and include a wide range of topics such as electric load models, electric vehicle charging, models for demand response, power management optimization and storage, pricing, and security.

The next-generation advanced metering infrastructure, with the aid of two-way smart meters, is expected to support advanced functions such as remote reading and control and demand response. In this paper, we thus focus on the design of a smart metering network (SMN) for a future scenario where data from residences/customer premises are dominated by electric vehicle charging traffic. Therefore, the well-suited multiple access control (MAC) protocol design for such event-driven data is an emerging research area. However, because the number of smart meters (communication nodes) involved in such a single SMN is much larger than those in today's local area networks, the traditional random access MAC protocol is unlikely to perform well. In order to solve this problem, we propose two grouping-based MAC protocols, namely, TDMA-DCF and group leader DCF-TDMA schemes, in this paper. These two schemes are directed at 802.11-type networks operating at frequencies below 1 GHz, which has been adopted by a new IEEE 802.11ah standardization task group. We also conduct the comprehensive throughput and delay analysis on these schemes for unsaturated traffic conditions and hidden node events. The numerical results show that these two grouping-based MAC protocols significantly outperform the traditional random access protocol DCF in a densely populated network with large coverage such as SMN.

Radio Frequency IDentification (RFID) is intended to supplant legacy (optical) bar code scanning technology found in many logistic and retail applications. RFID is distinguished by inexpensive, low power and compact form factor tags, whose longevity and efficacy are predicated on using passive communication techniques and on-tag power harvesting. Such tags employ backscatter modulation, which does not require any active RF components. As a result, backscatter has become an attractive design choice for short-range communications in power constrained wireless sensor networking scenarios. The purpose of this work is two-fold. First, it aims to expose backscatter communication as an emerging topic to a communication systems-theoretic audience. Since backscatter modulation and on-tag power harvesting efficiency are coupled, it is necessary to re-examine notions of power and spectral efficiency from an energy-constraint perspective; this leads to novel coded modulation schemes for future RFID systems. Further, we investigate RFID MIMO systems where the channel fading encountered has different statistics than the classical Rayleigh fading model. In turn,the trade off between diversity order and spatial multiplexing gains are distinct from wide-area MIMO.

One of the purposes of network tomography is to infer the status of parameters (e.g., delay) for the links inside a network through end-to-end probing between (external) boundary nodes along predetermined routes. In this work, we apply concepts from compressed sensing and expander graphs to the delay estimation problem. We first show that a relative majority of network topologies are not expanders for existing expansion criteria. Motivated by this challenge, we then relax such criteria, enabling us to acquire simulation evidence that link delays can be estimated for 30% more networks. That is, our relaxation expands the list of identifiable networks with bounded estimation error by 30%. We conduct a simulation performance analysis of delay estimation and congestion detection on the basis of l1minimization, demonstrating that accurate estimation is feasible for an increasing proportion of networks.

This work seeks to develop an analytical model for the per-node throughput analysis of IEEE 802.11 WLAN networks with hidden nodes by extending the Bianchi's model. With the analytic model we derive the per-node throughput of each node and quantify the impact of hidden nodes on per-node throughput. Through our analysis, we find that nodes having more hidden nodes are likely to have worse throughput performance than nodes having less hidden nodes, so resulting in unfairness in per-node throughput.

OFDMA femtocells are considered a key enabler in 3GPP LTE-Advanced networks of very high data rates for indoor users. However, the unmanaged nature of femtocells implies the need for careful modeling (and ultimately, managing) of inter-cell interference especially in dense deployments. So far, co-channel interference in femtocells has been investigated using traditional, cellular resource allocation approaches that usually assume a fully loaded network where the system is insensitive to the activity of a single user. This assumption is not suitable for femtocells which are designed to serve very few users and thus lacks the presumed traffic aggregation. In this paper, we exploit the bandwidth flexibility inherent to OFDMA to design more effective (distributed) random access MAC protocol for femtocells. The proposed Exponential Backoff in Frequency (EBF) algorithm allows femtocells to transmit packets in bulk and resolves collisions in the frequency-domain using a synchronized binary tree branching process over the channels that reduces the accessed bandwidth after every failed attempt. Analysis of the mean packet delay and simulation results show that EBF enjoys considerably less packet delay compared to the basic K-Aloha MAC in which femtocells transmit over a random K-subset of channels.

Network coding (NC), in principle, is a Layer-3 innovation that improves network throughput in wired networks for multicast/broadcast scenarios. Due to the fundamental differences between wired and wireless networks, extending NC to wireless networks generates several new and significant practical challenges. Two-way information exchange (both symmetric and asymmetric) between a pair of 802.11 sources/sinks using an intermediate relay node is a canonical scenario for evaluating the effectiveness of Wireless Network Coding (WNC) in a practical setting. Our primary objective in this work is to suggest pragmatic and novel modifications at the MAC and PHY layers of the 802.11 protocol stack on a Software Radio (SORA) platform to support WNC and obtain achievable throughput estimates via lab-scale experiments. Our results show that network coding (at the MAC or PHY layer) increases system throughput-typically by 20-30%.

This paper analyzes performance of RFID networks that are based on passive tags using EPC Gen2 Class1 communication protocol. For the first time, all the main factors impacting tag read efficiency and read latency are considered - inclusive of MAC layer collision, link layer packet loss and the impact of the use of energy harvesting in passive tags. Specifically, the impact of tag {duty cycling} due to limited harvested energy is considered - a first in the analysis of RFID systems, to the best of our knowledge.

In this work, the use of Space-Time Codes in passive Radio Frequency IDentification (RFID) systems is explored; this is feasible whenever a tag possesses multiple antennas. Information is encoded across the multiple tag antennas and received by an RFID reader, also typically equipped with multiple antennas. The nature of passive RFID induces a unique fading channel known as the dyadic backscatter channel, which differs statistically compared to the canonical Rayleigh fading channel. We introduce a modified dyadic channel for RFID backscatter that adequately captures the space-time coding paradigm. We then propose known orthogonal space-time codes and derive an upper bound on the the pairwise error probability (PEP), leading to estimates of the (asymptotic) diversity order. Interestingly, the diversity order is shown to depend only on the number of tag antennas but not the number of receive antennas; the resultant performance trade-offs is discussed. Lastly, simulation of the symbol error rates for different channel configurations are conducted to validate the analysis.

OFDMA is the basis of future broadband access, due to its many inherent advantages such as scalability and fine granularity for multi-user access. OFDMA-Aloha combines the flexibility of OFDMA with basic Aloha's collision resolution mechanism over sub-carriers, in an attempt to reduce packet collisions and achieve faster retransmission. However, this comes at the expense of a larger slot size, due to lower channel rates per subcarrier. The above gives rise to a fundamental question: whether to use a single wide-band Aloha channel and retransmit via random back-off in next K time slots, or to retransmit immediately in one of K narrow-band sub-channels which are each 1/K slower (OFDMA-Aloha)? We answer this question, by analyzing the two protocols: Aloha and OFDMA-Aloha under the same total bandwidth and load conditions. We first derive the exact distribution of the packet access delay of OFDMA-Aloha in the saturated case. Then, we extend the analysis to the unsaturated case and derive the mean queue length and packet delay by decomposing the system of interfering queues into multiple independent queues utilizing the symmetry in our system. Our results show that if the network is already saturated, channelization does not bring substantial reduction in the collision rate to the point where it outweighs the effect of expanded slot size. In this case the single channel Aloha performs better than OFDMA-Aloha especially when the gap between the number of channels and the number users is large. On other hand, when the network is lightly loaded, OFDMA-Aloha enjoys smaller packet delays, but not for long as it saturates faster than the single channel Aloha.

Data downloading on the fly is the base of commercial data services in vehicular networks, such as office-on-wheels and entertainment-on-wheels. Due to the sparse special distribution of roadside Base Stations (BS) along the road, downloading through Roadside-to-Vehicle (R2V) connections is intermittent. When multiple vehicles with geographical proximity have a common interest in certain objects to download, they can collaborate to significantly reduce their overall download time. In this paper, we investigate the application of Network Coding (NC) in collaborative downloading (CD). We focus on the R2V part of CD, and analytically derive probability distribution and the expected value of the amount of time necessary to deliver all of the information to the vehicles with and without NC. Our results show that using NC slightly improves the downloading time in addition to removing the need for having any sort of uplink communications from vehicles to the infrastructure.

A successful cognitive radio network (CRN) needs a fast and reliable spectrum sensing scheme to enable secondary users to utilise available channels. In this work, the authors first revisit conventional urn models for channel availability (the random independent identical distribution (i.i.d) models) and introduce a correlated Markov model which is apropos for scenarios with memory. After proposing an n-step serial search strategy, the authors investigate the performance of random and serial search schemes for the above occupancy models in terms of the mean number of steps for detection of an ‘open’ channel. The analytical results of the average detection are then presented for different sensing schemes under both random and correlated channel model. The authors then highlight a key trade-off underlying the overall mean time to detect a free channel: it is a function of both the mean number of steps and the sensing time per step. Reduced sensing duration in each step leads to lower detection probability (Pd) thereby increasing the average number of search steps required. This suggests that there exists an optimal sensing duration that minimises the overall mean detection time; this is analytically investigated (for low signal-to-noise ratio (SNR)) and verified by simulation results under various SNR environments.

The potential of successful cognitive radio networks operating in TV White Spaces (and other future bands re-allocated for unlicensed operation) has led to significant upsurge of interest in their design optimization - particularly those that are cross-layer in nature, involving both MAC protocols as well as physical layer aspects such as channel sensing. Typically, these seek to optimize a network-level metric (notably, aggregate throughput) of secondary (cognitive) network subject to interference constraints on the primary. In turn, this requires suitable sensing by cognitive users to detect availability of primary channels (currently unused by the protected incumbents) for opportunistic usage. To date, most studies have used largely hypothetical assumptions regarding channel idleness and resulting spectrum availability due to primary user dynamics. For example, idleness of channels over any spectrum are typically assumed to be an independent and identically distributed Bernoulli sequence. In contrast, nearly all real-time measurements suggest that channel idleness is frequency dependent, i.e., the probability that a channel is idle depends on the channel location. Cognitive radio research thus increasingly needs more realistic and validated models for channel idleness as the foundation of credible cross-layer analysis; this is the primary contribution of our work. We use two sets of real-time measurements conducted in disparate geographic locations over four distinct time intervals to show that channel idleness is appropriately modeled as independent but non-identical (i.n.i.d.) Bernoulli variables characterized by p_i, the probability of idleness for the i-th channel. We validate that Beta distribution can be used for modeling the variations in channel idleness probabilities; the Beta distribution parameters are estimated from the data to produce the best model fit. Based on the validated i.n.i.d. model, we build a predictive model by computing the availability probability of k channels, i.e, P{N_{idle} = k}, where N_{idle} denotes the number of idle channels over the spectrum of N channels. However, the combinatorial complexity inherent in the computation of P{N_{idle} = k} suggests the need for efficient approximations. We accomplish this by classifying idleness of channels based on the magnitude of p_i, and propose a novel Poisson-normal approximation for computing P{N_{idle} = k}. For validation, the distribution obtained from our technique is compared with the exact distribution and normal approximation using the approximation error criterion.

Data services for in-vehicle consumption are expected to become a primary driver in the development of future vehicular networks. Due to download rate limitations of present wide-area cellular connectivity such as 3G (the likely `pipe' to/from vehicles for long range connectivity), direct peer-to-peer data sharing among vehicles can supplement vertical downloading with horizontal dissemination. This paper studies the inter-vehicle data dissemination problem based on a WAVE/802.11p vehicular ad hoc network, using network coding. We first derive the probability mass functions (PMFs) of dissemination completion time in a prototypical three-node case for both random broadcast and with network coding, to quantify the benefits of the latter. For a one dimensional (1-D) infinite lattice network, we next provide analytical results for the steady state dissemination velocity of a data set, using network coding. The gains from such network coding, relative to the baseline scheme of random broadcast, and with perfect feedback, in presence of Rayleigh fading wireless links for this network are estimated using simulations.

Radio Frequency Identification (RFID) systems, presently standardized under EPC Global Class-1 Gen-2, have attracted increasing interest as the next-generation technology for tagged object identification. One of the important objectives of this work is to highlight the fact that the performance of the backscatter uplink (determined by constellation choice and forward error correction) is coupled to the downlink via the power harvesting functionality. The concept of normalized power loss per bit is introduced for such RFID communication systems to capture the consequent trade-offs, that form the crux of the results. We explore the use of higher dimensional (4-QAM) modulation schemes in future RFID systems (beyond current binary modulation in Class-1 Gen 2) as a means to improve uplink bit rate. However, this results in significantly increased normalized power loss vis-a-vis 2-PSK, suggesting a role for FEC coding. New coded modulation schemes - based on unequal error protection - are proposed that provides additional degrees of freedom (via choice of code parameters) to trade-off spectral efficiency with normalized power loss. This is explored and quantified, resulting in design recommendations.

In this paper, we consider a time slotted cognitive radio network where multiple secondary users (SUs) contend to access wireless channels. We propose and analyze a channel access policy where each secondary user stochastically determines whether to access a wireless channel (or not) based on a given access probability. In our analysis we consider two extreme cases - where all SUs a) possess full information and b) have no information regarding idle channels. We propose to obtain the access probabilities that minimize the steady-state queue length tail probabilities in the two extreme cases based on Effective Bandwidth theory. Our analysis provides an insight on how to design optimal channel access policies in the two extreme cases. We also show how the optimal channel access policies of two extreme cases are related with each other. Some numerical examples are provided to validate our analysis and investigate the performance behaviors of the optimal channel access policies.

Cognitive radio networks require fast and reliable spectrum sensing to achieve high network utilization by secondary users. Optimization approaches to spectrum sensing to-date have largely focused on maximizing throughput for secondary users while considering only a single parameter variable pertinent to sensing - notably the threshold or duration, but not both. In this work, we investigate the impact of true joint minimization under two performance criteria: a) minimization of the average time to detection of a spectrum hole and b) joint maximization of the aggregate opportunistic throughput. We show that the resulting non-convex problem is actually biconvex under practical conditions for which effective algorithms can be developed that yields reliable numerical procedures to solve the resulting optimization problem. The results show that the proposed approach can considerably improve system performance (in terms of the mean time to detect a spectrum hole and also the aggregate opportunistic throughput of both primary and secondary users), relative to the scenarios with only a single sensing variable or a sub-optimal ad-hoc optimization approach used for two variable case.

In this paper, we investigate a novel slotted ALOHA-based distributed access cognitive network in which a secondary user (SU) selects a random subset of channels for sensing, detects an idle (unused by licensed users) subset therein, and transmits in any one of those detected idle channels. First, we derive a range for the number of channels to be sensed per SU access. Then, the analytical average system throughput is attained for cases where the number of idle channels is a random variable. Based on that, a relationship between the average system throughput and the number of sensing channels is attained. Subsequently, a joint optimization problem is formulated in order to maximize average system throughput. The analytical results are validated by substantial simulations.

Data services for in-vehicle consumption are expected to become a primary driver in the development of future vehicular networks. Due to download rate limitations of present wide-area cellular connectivity such as 3G (the likely 'pipe' to/from vehicles), direct peer-to-peer data sharing among vehicles can supplement vertical downloading. This paper studies the inter-vehicle data dissemination problem in a WAVE/802.11p vehicular ad hoc network, using network coding (NC). The gains from such NC, relative to a baseline scheme of random transmission, is estimated using analysis and simulations.

In Dedicated Short Range Communications (DSRC) based vehicular networking, each vehicle periodically broadcasts control updates (that contain location and speed information etc.) to its neighbors, as a key component of traffic management and safety applications. The effectiveness of such a broadcast feature can be measured by two metrics: (1) the efficiency, or the average rate (number of nodes per sec) to which a source can deliver its broadcast packets, and (2) the reliability, or the average number of nodes that receive a specific transmission successfully. We demonstrate theoretical limits to and achievable tradeoffs between efficiency and reliability for a linear network under Rayleigh fading links. We then provide power control and congestion control strategies that maximize broadcast efficiency. A strategy that achieves near-optimal broadcast efficiency when the network nodes have high mobility is also described. Ns-2 simulations are used to validate our analytical results.

In network tomography, we seek to infer link parameters inside a network (such as link delays) by sending end-to-end probes between (external) boundary nodes. The main challenge here is to estimate link-level attributes from end-to-end measurements. In this paper, based on the idea of combinatorial compressed sensing, we specify conditions on network routing matrix under which it is possible to estimate link delays from measurements of end-to-end delay. Moreover, we provide an upper-bound on the estimation error.

Cognitive radio networks require fast and reliable spectrum sensing to achieve high network utilization by secondary users. Current optimization approaches to spectrum sensing to-date have focussed on maximizing aggregate throughput while considering only a single parameter variable pertinent to sensing, notably the threshold or duration, but not both. In this work, we consider joint minimization of the average detection time for finding a spectrum hole as a function of both parameters. We show that the resulting non-convex problem is actually biconvex under practical conditions and solve for a global optimum detection time. Numerical results show that the proposed approach can considerably improve system performance in terms of the mean time to detect a spectrum hole.

Reliable and timely multi-hop propagation of messages among vehicles is essential for a safer and greener transportation system. Various broadcast-based forwarding strategies are envisioned for infrastructure-less vehicle-to-vehicle (v2v) communications. This paper proposes a prioritized broadcast contention control (PBCC) module/layer that provides reliable and low latency multi-hop connection. The PBCC forwarding algorithm optimizes the back-off distribution to improve the probability of successful broadcast and prioritizes forwarders based on location information. This module can be implemented in WAVE devices with minimum system modification. We integrate simple vehicular mobility models into ns-2 and implement a WAVE/802.11p communication protocol stack. Extensive simulations demonstrate PBCC's superiority in multi-hop delay.

In a vehicular network, every vehicle broadcasts update messages that contain location and speed information periodically to its one hop neighbors. The broadcast efficiency measures the average rate at which a vehicle receives these packets from any of its neighbors. As the node density increases, heightened interference lowers broadcast efficiency if congestion control mechanism is not used. In this paper, we analyze the broadcast efficiency under Rayleigh fading channel, and provide congestion control and power control strategies that maximize the efficiency. A worst-case guaranteed strategy achieving at least 95% of the optimal is also provided for cases when the network nodes have high mobility. Ns-2 simulations show that our analytical results accurately predict the system dynamic.

In network tomography, we seek to infer link status parameters (delay, congestion, loss rates etc.) inside a network through end-to-end measurements at (external) boundary nodes. As can be expected, such approaches generically suffer from identifiability problems; i.e., status of links in a large number of network topologies is not identifiable. We introduce an innovative approach based on linear network coding that overcomes this problem. We provide sufficient conditions on network coding coefficients and training sequence under which any logical network is guaranteed to be identifiable. In addition, we show that it is possible to locate any congested link inside a network during an arbitrary amount of time by increasing size of transmitted packets, leading to raise in complexity of the method. Further, a probability of success is provided for a random network. OPNET is used to implement the concept and confirm the validity of the claims — simulation results confirm that LNC correctly detects the congested link in situations where standard probing based algorithm fails.

The next generation internet will be the internet of things (and not just of computing devices like PCs, PDAs); this is presumed to be enabled by integrating simple computing plus communications capabilities into common objects of everyday use. Radio-frequency identification (RFID) is a compelling technology for creation of such pervasive sensor networks due to its potential for ubiquitous, low-cost/low-maintenance use. However, the current drivers for RFID deployment emphasize supply chain management using passive tags, implying that RFID sensor nets require advances beyond the components and system designs aimed at supply chain applications. This work provides a glimpse of how this may be achieved.

Dynamic Spectrum Access (DSA) has the potential to vastly improve spectrum utilizations among heterogeneous networks. We present a continuous-time Markov chain (CT-MC) model to analyze the performance of three co-located cognitive systems with various priority classes and bandwidth requirements. The maximum spectrum utilization and minimum blocking probability are derived in a one-channel band scenario. A channel packing scheme (CPS) is then proposed in a multiple-channel band scenario. This scheme packs users of smaller bandwidth requirements in clusters, in order to alleviate the unnecessary blockage to users of larger bandwidth requirements. Numerical results show that the system can benefit from CPS in terms of blocking probability, spectrum utilization and overall failure probability.

Although several cooperative diversity strategies have been proposed for simple 2-hop multiple-relay networks, practical and efficient strategies that guarantee maximum diversity order for arbitrary, multi-hop amplify-and-forward relay networks are not yet available. In this paper, the maximum achievable diversity order for a given connectivity is shown to be determined by the number of links on the minimum cut set, and achieved by a selection strategy which maximizes end-to-end SNR. The optimal selection requires the channel information of all the links and serves as a performance bound. A sub-optimal selection method is then proposed to achieve full diversity in a distributed and low-complexity manner. The performance loss of the sub-optimal selection is shown to be small by both theoretic analysis and simulations.

This paper introduces two new tree-based anti- collision schemes using multiple feedback symbols for uplink tag random access of emerging radio frequency identification (RFID) networks. To this end a uplink(UL) time slot requires an extra time portion called voting field in addition to the packet payload to obtain a slot based estimate for the number of contending tags. As a function of the voting field length we examine MAC efficiency improvements in terms of UL throughput, and compare it with the conventional binary tree based RFID MAC in ISO 18000-6 Type B standard.

Dynamic spectrum access (DSA) is a promising approach for the more effective use of existing spectrum. Of fundamental importance to DSA is the need for fast and reliable spectrum sensing over a wide bandwidth. A model for two-stage sensing is described based on an analysis of the mean time to detect an idle channel. Simulation results show that it provides significantly faster idle channel detection than conventional single-stage random searching. Several system-level issues are also investigated including the settling time of the phase-locked loop (PLL) in the frequency synthesizer, which determines the channel switching time. Effects of the bandwidth of the coarse sensing block and the integration duration of the energy detector are also presented.

Dynamic spectrum access (DSA) is a promising approach for mitigating spectrum scarcity. Underlying DSA is the need for fast and reliable spectrum sensing over a potentially large band. In N.M. Neihart, et al., (May 2007), the concept of two-stage sensing scheme was introduced. In this work, we develop models for performance analysis based on mean time to detect an idle channel. Simulation results show that two-stage sensing leads to faster detection than conventional single-stage random search. System-level issues such as the impact of bandwidth of coarse sensing block and sensing duration of energy detector on mean detection time are also explored.

In high density (HD) WLANs, packet losses can occur due to hidden terminals (asynchronous interference) or collisions (synchronous interference). Without differentiating above packet losses, the standard backoff algorithm of IEEE 802.11 with binary exponential backoff (BEB) can greatly degrade throughput and fairness. In this work, we exploit differentiated PER (packet error rate) to propose a novel CWTO (joint contention window and transmission opportunity) adaptation algorithm to improve the aggregate throughput as well as network fairness for multi-cell HD WLANs. Contention window and transmission opportunity adaptation are dedicated to throughput maximization and fairness provision respectively and their effectiveness supported by extensive simulation results.

The importance of suitable link-aware routing metrics for multi-hop (mesh) wireless networks is well-established. Channel-to-link assignments impact the distribution of co- channel links and contribute to inter-flow and intra-flow interference. In this paper we present a new location-aware routing metric (ALARM) that better captures the resulting co-channel interference as a function of channel assignments. The link metrics used are sensitive to the location of nearby co-channel links that are within interference or carrier sensing range; these can be pre-calculated and used with any routing algorithm. The performance of ALARM is compared with weighted cumulative expected transmission time metric (WCETT) via OPNET over a comprehensive range of network parameters for linear and 2-D grid topologies.

We address several inter-related aspects of underwater network design within the context of a cross-layer approach. We first highlight the impact of key characteristics of the acoustic propagation medium on the choice of link layer parameters; in turn, the consequences of these choices on design of a suitable MAC protocol and its performance are investigated. Specifically, the paper makes contributions on the following fronts: a) Based on accepted acoustic channel models, the pointto- point (link) capacity is numerically calculated, quantifying sensitivities to factors such as the sound speed profile, power spectral density of the (colored) additive background noise and the impact of boundary (surface) conditions for the acoustic channel; b) It provides an analysis of the Micromodem-like linklayer based on FH-FSK modulation; and finally c) it undertakes performance evaluation of a simple MAC protocol based on ALOHA with Random Backoff, that is shown to be particularly suitable for small underwater networks.

Abstract Recently, multi‐radio mesh technology in wireless networks has been under extensive research. This is because of its potential of overcoming the inherent wireless multi‐hop throughput, scalability and latency problems caused by the half‐duplex nature of the IEEE 802.11. The concept of deploying multiple radios in wireless network access points (APs) has shown a promising way to enhance the channel selection and the route formation while the MESH topology allows more fine‐grained interference management and topology control. Within this realm, given a set of end‐to‐end objectives, there are multiple issues that need to be identified when we consider the optimization problem for fixed multi‐channel multi‐hop wireless networks with multiple radios. This paper addresses the static channel assignment problem for multichannel multi‐radio static wireless mesh networks. We first discuss its similarities and differences with the channel assignment problem in cellular networks (WMN). Next, we present four metrics based on which mesh channel assignments can be obtained. Three of these metrics attempt to maximize simultaneous transmissions in a mesh network, either directly or indirectly. The fourth metric quantifies the ‘diversity’ of a particular assignment and can be used as a secondary criterion to the other three metrics. Related optimization models have also been developed. Copyright © 2007 John Wiley & Sons, Ltd.

We propose a contention based reservation MAC protocol for a collaborative sensing scenario involving a set of surveillance UAVs communicating with a hub. Data transmission rights are secured via distributed contention access between the UAV nodes for K available mini-slots. Each node chooses a slot with probability p independently of the others and is only allowed one attempt in a frame. We investigate the optimal choice of p which maximizes the one-shot probability of success(or alternately, the expected number of successes), beta, over the K minislots. We show that beta is prone to local maxima and develop an empirical formula based on goodness-of-fit which matches the numerically obtained values closely.

The growing adoption of 802.11 networks in the enterprise segment has led to the emergence of High Density (HD) WLAN scenarios where large (100-1000) numbers of clients are serviced by 10-100s of APs in a multi-cell environment. This leads to an interference limited environment due to limited spectrum availability; hence network design for throughput scalability becomes the primary design challenge. Current industry practice leans towards centralized RF management of HDWLAN Enterprise deployments using a RF controller. The main focus of the work in this paper is a new CS/RT (Carrier Sense/Receiver threshold) adaptation algorithm in which APs, Clients and RF controllers participate collaboratively to mitigate the interference. Performance comparisons of the proposed CS/RT adaptation compared with current rate adaptation algorithms such as SampleRate [2] and ARF [1] are presented.

The relevant performance metric for successful deployment of radio frequency identification (RFID) systems for tag inventory applications is the latency for reading all tags with (high) reliability. Tag collisions in response to a reader query increase the read latency of the MAC protocol; the mean latency can be considerably improved by a combination of techniques including more efficientanti-collisionapproaches as well as via estimationofthenumberofbackloggedtags. We propose a novel anti-collision algorithm:breadth-first-searchwithm-arysplitting(BMSA) within a TDMA frame structure. A simple backlogged tag estimation algorithm is used in conjunction with the above to dynamically set thesplittingfactor(SF) m. Simulation results demonstrate the superiority of the proposed scheme over existing methods in terms of throughput/latency.

Carrier sense multiple access (CSMA) protocols require stations that wish to transmit to first check the shared medium for ongoing transmissions. However, in wireless networks stations may not be able to sense transmissions from all other stations; hence those at different locations can experience different amounts of contention, resulting in unfairness and possible "starvation" (inability to acquire channel access for long periods). In this paper we model how the 802.11 MAC protocol allocates bandwidth among multiple saturated flows in a linear topology when not all senders are within sensing range. We consider a specific class of topologies consisting of n independent flows, where each sender can sense k neighbors on either side. Our work uncovers global interactions among flows leading to startling sensitivities in node throughput. A new model to predict the long-term throughput of each flow under saturation is presented and our model results validated via OPNET simulations.

This paper addresses the design challenge of interference mitigation in the emerging high density (HD) wireless LAN. It is proposed to differentiate interference according to theirenergyandtimingrelative to desired signal, and measure packet error rate (PER) locally at transmitter for each type of interference. Then,self-adaptationalgorithms are designed to adjust a) clear channel assessment (CCA) threshold, aka physical carrier sensing threshold, to leverage spatial reuse for achieving higher aggregate throughput, and b) transmit power (TP) to compensate location difference among links, and prevent individual links from starving. Compared to an end-to-end (E2E) feedback loop, ours has negligible complexity and zero over-the-air overhead. Extensive OPNET simulations are used to compare the performance of our solutions against the legacy and the ideal.

In high density (HD) mesh networks, packet losses can occur due to co-channel interference (asynchronous interference) or collisions (synchronous interference). In this paper, we first propose a novel method of estimating the probability of collision and interference statistically. Further, we integrate this differentiation method with physical carrier sensing adaptation in a novel centralized algorithm to improve the aggregate throughput in HD mesh network. Extensive simulations results show that the on-line algorithm approaches the optimal throughput predicted by analytical models.

In this paper, a new clear channel assessment (CCA) method: cascaded-CCA, is proposed that is apropos for next generation cognitive radios. The primary motivation for the proposed approach is to integrate the respective advantages of two 'standard' CCA mechanisms (energy detection and preamble detection) to arrive at a new dual-threshold CCA family that can provide greater flexibility towards tuning MAC performance. The performance of cascaded-CCA is explored via MATLAB simulations that implement the CCA modules and medium access control (MAC) protocol for IEEE 802.11 and IEEE 802.15.4 as representative examples.

A parallel, multi-resolution spectrum sensing technique that is amenable to multiple-antenna cognitive radios is introduced. The authors show that for energy-detector-type spectrum sensors, the total sensing time due to FFT latency is reduced by 100 times using the proposed method versus the fixed-resolution, serial detection method employed in single-antenna systems. System-level tradeoffs such as the number of antennas, sensing bandwidth, and FFT size are also explored.

The recent ratification of IEEE 802.15.4 PHY-MAC specifications for low-rate wireless personal area networks represents a significant milestone in promoting deployment of wireless sensor networks (WSNs) for a variety of commercial uses. The 15.4 specifications specifically target wireless networking among low-rate, low-power and low-cost devices that is expected to be a key market segment for a large number of WSN applications. In this article, we first analyze the performance of the contention access period specified in the IEEE 802.15.4 standard in terms of throughput and energy consumption. This analysis is facilitated by a modeling of the contention access period as nonpersistent CSMA with backoff. We show that, in certain applications in which having an inactive period in the superframe may not be desirable due to delay constraints, shutting down the radio between transmissions provides significant savings in power without significantly compromising the throughput. We also propose and analyze the performance of a modification to the specification which could be used for applications in which MAC-level acknowledgements are not used. Extensivens-2 simulations are used to verify the analysis.

The combination of multiple radio nodes in con junction with a suitably structured multi-hop or mesh architecture has the potential to solve some of the key limitations of present day wireless access networks that are based on single-radio nodes. This paper addresses the static channel assignment problem for multi-channel multi-radio static wireless mesh networks. We present four metrics based on which mesh channel assignments can be obtained. In particular, we focus on minimization of the average and maximum collision domain sizes and show that these problems are closely related to problems in combinatorial optimization such as MAX k-CUT and MIN k- PARTITION. We also present heuristic algorithms for solving the channel assignment problems using the above two metrics.

Clear channel assessment (CCA) is an essential ingredient in wireless networks employing channel sensing as part of their medium access mechanism. While CCA itself is implemented at the PHY layer, the primary impact of its performance/complexity is on MAC metrics like throughput and energy efficiency; this cross-layer dependency makes it necessary to enhance MAC protocol performance evaluation by considering the specifics of CCA implementation that are naturally link-dependant. We perform such a cross-layer evaluation of the impact of CCA on MAC performance for the specific case of IEEE 802.15.4 standard for WPANs and derive some heuristics to choose the type of CCA and its parameters based on traffic and channel conditions to realize improved MAC performance.

Adaptive physical carrier sensing (PCS) based on tuning the PCS threshold has been shown to be an effective mechanism for improving aggregate network throughput. However, earlier work assumed a single link rate and a common PCS threshold for the entire network, as appropriate for a regular 2-D lattice grid of nodes with constant link (1-hop) distances. In an ad-hoc network topology, the 1-hop link distances vary significantly and a single PCS threshold is no longer suitable. Because IEEE 802.11 a/b/g networks provide multiple data rates over any link, joint tuning of the link rate and PCS threshold is thus desirable for achieving optimal aggregate throughput for ad-hoc networks. In this work, we first propose a simple yet effective principle for the above optimization. Next, we use the intuition offered by these formulations to suggest run-time adaptive solutions in OPNET simulations. We restrict ourselves to 1-dimensional random linear networks primarily to corroborate analysis with simulations and defer results with other topologies for future work

Very high rate packet data systems such as those based on wideband spread-spectrum (SS) signaling face an important challenge - achieving fast and reliable acquisition to minimize preamble overhead and optimize packet throughput. Such wideband modulation schemes undergo frequency selective fading, implying a very large number of resolved multipath components. Thus, the conventional analyses of serial search acquisition schemes based on simplifying assumptions that are valid in narrow(er) band systems (and are invalid for sufficiently wideband systems) need to be revamped. Also, there is a need to devise new schemes that exploit the presence of multipath components for faster acquisition over simple serial search. Our work provides novel contributions in both these aspects: we analyze serial and random search acquisition schemes and compare their performances in several multipath environments. It is shown that over many typical indoor channels, random search offers significantly lower mean acquisition times

The drive towards portable wireless devices capable of forming ad-hoc wireless networks on demand has spurred significant interest in the design and analysis of power-efficient schemes at all layers of the protocol stack. In order to increase useful lifetimes of such battery-powered devices, it is vital to understand the role of carrier-sense based multiple access protocols in controlling the trade-offs between throughput and energy consumption performance. Our focus in this work is the impact of imperfect carrier sensing on this trade-off; accordingly, we present an analysis of the energy efficiency of p-persistent CSMA with carrier sense imperfections

We propose a mesh (multi-hop) architecture based on two-radio 802.11 access points (AP) and examine achievable aggregate throughput by exploiting spatial reuse and multiple channels. A suitable distributed clustering is used to self-organize the network for channel allocation; all communications between nodes in the same cluster (intra-cluster) use the secondary radio and a common channel whose selection is based on an algorithm that minimizes the cochannel interference (CCI). This dramatically reduces complexity compared to per-packet channel switching approaches. All intercluster communications are performed on a common channel using the default (primary) radio. Backward compatibility is guaranteed by allowing legacy single-channel APs to connect to the new two-radio devices through the common default radio. Simulation results for large-scale IEEE 802.11b networks demonstrate the significant improvement in one-hop aggregate throughput. Specifically, the new two-radio multi-channel mesh solution more than doubles the aggregate throughput compared to the traditional single-radio single-channel mesh.

The choice of physical carrier sensing (PCS) threshold is key to the trade-off between the amount of spatial reuse and probability of packet collisions in a wireless ad hoc network. In this paper, we present a new analytical approach for optimizing the PCS threshold as measured by probability of packet collisions and the aggregate one-hop throughput. Our model simultaneously incorporates the impact of PCS threshold and the backoff mechanism via a suitable Markov chain model for saturation (i.e. all nodes always have a packet to send in their queues). Elaborate OPNET simulation results show the effectiveness of the analytical model

Abstract — The combination of multiple radio nodes in conjunction with a suitably structured multi-hop or mesh architecture has the potential to solve some of the key limitations of present day wireless access networks that are based on single-radio nodes. This paper addresses the channel assignment problem for multi-channel multi-interface (radio) wireless mesh networks. We focus on static wireless mesh networks where multiple nonoverlapping channels are available for each wireless interface. In this network environment, our objective is to find a fixed channel assignment which maximizes the number of bidirectional links that can be activated simultaneously, subject to interference constraints. We present two mixed integer linear programming models for solving the fixed channel assignment problem with multiple radios. Detailed computational results on various grid topologies are also presented and discussed. I.

Very high rate packet data systems, such as those based on ultra-wideband (UWB) signaling, face an increasingly important challenge - achieving fast timing acquisition and synchronization (which must be done typically on an individual packet basis) to minimize preamble overhead and optimize (packet) throughput. Impulse based UWB modulation schemes use short (nano-second) time-duration pulses that are appropriately shaped - the resulting high resolution in time implies that the acquisition algorithm must employ sub-pulse duration steps, thereby leading to a large search space if a serial timing acquisition approach is used. Moreover, owing to the strict average transmit power limitations on UWB transmissions resulting from the Part 15 limits imposed by the FCC, a large number of pulses need to be integrated for reliable acquisition decisions, which consequently leads to large mean acquisition times (MAT). We investigate the performance of the conventional serial search and random search schemes applied to the acquisition of UWB signals in multipath environments. It is shown that over typical UWB multipath channels, a random search scheme may yield lower MAT than serial search.

In this paper, we consider a multicell MIMO-OFDM TDD system where the emphasis is on the downlink for future data-intensive applications. We propose a MIMO scheme that can effectively combat co-channel interference with only local BS coordination and retain the high peak rate achievable for point-to-point single-cell communications. We describe several different levels of CSI availability at both the transmitter and the receiver that lead to different system architecture choices. The performance of rate-1 SFBC code (Shao et al. (2004)) with channel estimation is investigated via simulation; our results show that with pragmatic channel estimation schemes, multi-cell MIMO-OFDM is a good candidate for future high-rate applications.

To provide new and/or higher rate wireless services with limited spectrum resources, frequency overlay has been naturally proposed to accommodate the new and legacy systems in a common band. We address the multiuser detection problem for overlaid code-division multiple-access (CDMA) scenarios. However, in contrast to the well-studied conventional single-rate CDMA, miscellaneous systems overlay almost always indicates the presence of multirate traffic that introduces an additional degree of freedom in receiver design-i.e., differences in the symbol rates. We concentrate on receiver design for multirate traffic, while assuming a lack of information exchange between the constituent (new and legacy) systems, as is commonplace in practice. We propose a receiver architecture based on linear parallel interference cancellation where the out-of-rate intersystem interference is estimated and subtracted by means of its characteristic subspace, thereby avoiding the need for the exact knowledge of signature waveforms of the interfering system. Simulation results validate our solution and show that the proposed receiver has better performance in various aspects than several other solutions for the same purpose.

We propose a novel rate-one (i.e., one symbol per transmission), space-frequency block code (SFBC) for an orthogonal frequency division multiplexing (OFDM) system with transmit (M), and receive (N) antennas that achieves the maximum diversity attainable over frequency-selective channels. Moreover, the space-frequency (SF) code design is shown to be robust to overestimation of the (true) channel order L at the price of increasing decoding complexity. Further, even if the channel order is underestimated (K

Achieving higher link rates in support of newer services and increasing range are the two main goals for next generation wireless LAN networks. This work primarily contributes to a high rate solution, based on a novel extension to the rate-1 space-frequency block code (SFBC) design in L. Shao et al. (Dec. 2003) to full rate case. To further improve performance without increasing complexity, we propose unequal power allocation at the transmitter with no requirement of channel knowledge. Compared with standard 802.11a transmitter which uses convolutional code with a single transmit antenna and antenna selection diversity among 2 receive antennas with soft Viterbi decoding, we show that our HR-SFBC code with 2 transmit antenna not only doubles the throughput (as expected) but also provides additional link margin (and hence improves range).

This paper focuses on improving performance of land mobile satellite channels (LMSCs) at high band (Ka-band or EHF band), where shadowing is the primary impediment to reliable data transmission. Compared with multipath fading, shadowing exists on a longer time scale; hence, interleaving to combat shadowing introduces unacceptably large decoding delay. We use Lutz's model to investigate bit-error rate/packet-error rate (BER/PER) performance of interleaving with various forward error correction (FEC) coding as a function of different channel parameters to demonstrate its limited effectiveness for combatting burst errors whose mean duration significantly exceed a link layer (LL) packet. We propose a delayed two-copy selective repeat ARQ (DTC-SR-ARQ) scheme, whereby two copies of a packet are sent-the second with a delay relative to the first-in every transmission or retransmission. Closed-form expressions for mean transmission time, success probability, and residual loss probability are provided and simulations used to validate the analysis. Furthermore, the issue of optimum delay is addressed as well, and a simple yet effective strategy is suggested to support transmission control protocol (TCP) traffic over this data link layer. DTC-SR-ARQ is shown to achieve much shorter additional delay than interleaving and compared with normal SR-ARQ, reduces mean transmission time at expense of a small increase in residual packet loss probability. Furthermore, ns2 simulation results show that for TCP traffic, DTC-SR-ARQ acquires higher end-to-end throughput than normal SR-ARQ.

The paper provides a tutorial overview of ultrawideband (UWB) radio technology for high-speed wireless connectivity. Subsequent to establishing a historical and technological context, it describes the new impetus for UWB systems development and standardization resulting from the FCC's recent decision to permit unlicensed operation in the 3.1-10.6 GHz band subject to modified Part 15 rules and indicates the potential new applications that may result. Thereafter, the paper provides a system architect's perspectives on the various issues and challenges involved in the design of link layer subsystems. Specifically, we outline current developments in UWB system design concepts that are oriented to high-speed applications and describe some of the design tradeoffs involved.

Transmitter/receiver optimization for a generic narrowband overlay communication scenario is addressed. The overlay and existing legacy systems are assumed to occupy the same frequency bands for spectral efficiency, thus introducing cochannel interference; however, the new and legacy systems are assumed to be noncooperative, as is appropriate for some pragmatic scenarios. A composite figure of merit is used consisting of a weighted sum of the mean-squared error (MSE) of the (new) overlay system plus the excess MSE in the legacy system caused by the introduction of the overlay system. Necessary conditions on the transmitter and receiver that jointly optimize the above metric are derived. The effects of varying key parameters such as the loop length (range) and transmitter power are investigated via computational examples.

Abstract Spatial reuse in a mesh network can allow multiple communications to proceed simultaneously, hence proportionally improve the overall network throughput. To maximize spatial reuse, the MAC protocol must enable simultaneous transmitters to maintain the minimal separation distance that is sufficient to avoid interference. This paper demonstrates that physical carrier sensing enhanced with a tunable sensing threshold is effective at avoiding interference in 802.11 mesh networks without requiring the use of virtual carrier sensing. We present an analytical model for deriving the optimal sensing threshold given network topology, reception power and data rate. A distributed adaptive scheme is also presented to dynamically adjust the physical carrier sensing threshold based on periodic estimation of channel conditions in the network. Simulation results are shown for large‐scale 802.11b and 802.11a networks to validate both the analytical model and the adaptation scheme. It is demonstrated that the enhanced physical carrier sensing mechanism effectively improves network throughput by maximizing the potential of spatial reuse. With dynamically tuned physical carrier sensing, the end to end throughput approaches 90% of the predicted theoretical upper‐bound assuming a perfect MAC protocol, for a regular chain topology of 90 nodes. Copyright © 2004 John Wiley & Sons, Ltd.

A novel rate-1, space-frequency (SF) code for an orthogonal frequency division multiplexing (OFDM) system with transmit (M) and receive (N) antennas that achieves the maximum diversity attainable over frequency-selective channels is proposed. Since the SF code symbol is transmitted in one OFDM block duration, it has smaller processing delay than previously proposed space-time-frequency (STF) block codes.

In this paper, we focus on the performance of TCP splitting in satellite-terrestrial hybrid networks. By simulation we show that long-time link outage has great negative impact on TCP throughput. To solve the problem, an ACK reservation scheme is proposed to speed up TCP recovery from link outage and analytical estimate of a key parameter of the scheme is provided for achieving high end-to-end TCP throughput. Simulation results validate our analysis, and show that after the end of link failure, the TCP source can be re-started using ACK reservation with virtually no additional lag leading to great improvement on bandwidth utilization and end-to-end throughput.

In this paper, we propose an analytical model for TCP over selective repeat ARQ in wireless networks, in which random loss is the primary impediment to reliable, high-speed data services. We focus on the issue of modeling RTT (round trip time) variation due to ARQ retransmission at the link layer with non-negligible propagation delay. With the proposed model, we present upper and lower bounds for TCP end-to-end throughput. Simulation with ns2 is performed to validate our analysis.

In TDMA-based MAC (media access control) protocols for satellite network access, slotted ALOHA which has been widely deployed in very small aperture terminal (VSAT) systems. More recently, generalized retransmission announcement protocol (GRAP) was proposed, which regroups the immediate access by contention at low loads and the reservation access at higher loads to achieve a better efficiency. Inspired by GRAP, we propose a new MAC protocol (CA-GRAP) using cumulative acknowledgment (CA) technique to further improve the success probability of reservation request. Furthermore, the efficiency random access in CA-GRAP is improved by introducing contention index. Our proposal does not require collision or error detection but is based only on correctly received packets, dramatically simplifying the procedure. The impact of all these protocols on TCP traffic is investigated and an upper bound of TCP throughput at high loads is derived for GRAP-based protocols. Simulation results show that our new method significantly outperforms GRAP.

The primary contribution of this work lies in the derivation of the exact characteristic function (and hence, the mean and variance) of the capacity of multiple-input multiple-output (MIMO) systems for semicorrelated flat-fading channels. A Gaussian approximation to the exact capacity results is suggested and evaluated for its accuracy. We show that over a range of correlation levels this approximation is adequate even for moderate numbers of transmit and receive antennas.

A link model-driven approach toward transmission control protocol (TCP) performance over a wireless link is presented. TCP packet loss behavior is derived from an underlying two-state continuous time Markov model. The approach presented here is (to our knowledge) the first that simultaneously considers (1) variability of the round-trip delay due to buffer queueing; (2) independent and nonindependent (bursty) link errors; (3) TCP packet loss due to both buffer overflow and channel errors; and (4) the two modes of TCP packet loss detection (duplicate acknowledgments and timeouts). The analytical results are validated against simulations using the ns-2 simulator for a wide range of parameters; slow and fast fading links; small and large link bandwidth-delay products. For channels with memory, an empirical rule is presented for categorizing the impact of channel dynamics (fading rate) on TCP performance.

Reliable channel estimation is indispensable for orthogonal frequency-division multiplexing (OFDM) systems employing coherent detection and adaptive loading in order to achieve high data rate communications. Several options exist in practical OFDM systems-including training symbols, cyclic prefix, virtual carriers, pilot tones, and receiver diversity-to facilitate channel estimation. In this paper, a subspace blind channel estimation method based on exploiting the presence of virtual carriers is proposed for OFDM systems over a time-dispersive channel. The method can be applied to conventional OFDM systems with cyclic prefix as well as OFDM systems with no cyclic prefix. The reduction/elimination of cyclic prefix thereby provides the OFDM systems the potential to achieve higher channel utilization than most previously reported cyclic prefix based estimators. Sufficient channel identifiability condition is developed as well. Comparison with two other recently reported subspace methods is presented via computer simulations to support the effectiveness of the proposed method.

Most previously reported carrier frequency off-set (CFO) estimation algorithms for OFDM systems rely on the assumption of sufficient cyclic prefix (CP) - i.e. the channel length is less than the length of CP. In practice, this can be violated leading to significant performance degradation characterized by an irreducible error floor due to model mismatch. This paper focusses on CFO estimation for uncompensated ISI channels - it introduces a modified signal model and by exploiting the special structure of the filtering matrix due to CP and virtual carriers, a novel subspace CFO estimator is proposed. The method is attractive for its low complexity by avoiding SVD computation and potential to achieve high channel utilization by decreasing the length of CP in ISI channels. Preliminary computer simulations illustrate the effectiveness of the proposed algorithm.

In this paper, we investigate the impact of applying the channel estimation method in [1] to an OFDM system equipped with rate 1 nonorthogonal space time block code for K transmit and 1 receive antennas. A new training pattern based on the Hadamard construction is designed that enables estimation of the K channels separately and thus reduces the effective noise variance in the estimate. The simulation result shows that using this low rank channel estimation in frequency selective slow fading channels yields very good BER performance comparable to the case when channel is known at the receiver. Moreover, the use of rate 1 non-orthogonal STBC achieves significantly superior performance vis-a-vis Alamouti's orthogonal STBC.

In this paper, we use Lutz's (1991) model to investigate BER (bit error rate)/PER (packet error rate) performance of the LMSC channel with various FEC (forward error correction) coding as a function of different channel parameters. The problem of insufficient interleaving is studied. Next, hybrid FEC/ARQ techniques are evaluated for different (i.e. open, and rural) channels. We focus on the problem of joint optimization of system parameters, such as maximum retransmission number, and coding rate. Simulation results show that hybrid ARQ with proper parameters guarantees high TCP end-to-end throughput performance, and is a promising approach for high-speed satellite communications in the future.

Systems using ultra-wideband (UWB) technology have been shown to achieve very high data rates (100 Mbps and above) for short-range, indoor applications. UWB signals exhibit a number of performance advantages in terms of multipath resolution and fading reduction. However, UWB systems can also exhibit significant implementation complexity in timing, synchronization, and signal correlation. This paper presents a differential detector that rakes in some of the multipath energy, while relaxing some of the stringent implementation requirements. We analyze the performance and the implementation of the differential detector, and compare it to a RAKE receiver with a correlator detector in the presence of AWGN and multipath.

Multi-rate CDMA is a potentially attractive multiple access method for future broad-band multimedia wireless networks that must support integrated voice/data traffic. The primary impairment for such multi-rate systems is the multipath nature of radio channels that results in intra-user inter-chip interference (ICI) and multi-user interference (MUI) between different users' symbols. Explicit knowledge of the channel is typically needed for high performance detectors (such as coherent demodulation). We propose a subspace method for channel estimation in multi-rate CDMA systems. A unified signal model that applies to three multi-rate CDMA schemes proposed in the literature is developed. The computational complexity for multi-rate scenarios is large and variable-accordingly, a modified approach is devised that offers performance/complexity trade-offs. Performance analysis is conducted based on a close-form expression for the mean square error of the estimator, supported by simulation results that investigate the effectiveness of our method.

We consider the scenario of using Automatic Repeat reQuest (ARQ) retransmission for two-way low-bit-rate video communications over wireless Rayleigh fading channels. Low-delay constraint may require that a corrupted retransmitted packet not be retransmitted again, and thus there will be packet errors at the decoder which results in video quality degradation. We propose a scheme to improve the video quality. First, we propose a low-delay interleaving scheme that uses the video encoder buffer as a part of interleaving memory. Second, we propose a conditional retransmission strategy that reduces the number of retransmissions. Simulation results show that our proposed scheme can effectively reduce the number of packet errors and improve the channel utilization. As a result, we reduce the number of skipped frames and obtain a peak signal-to-noise ratio improvement up to about 4 dB compared to H.263 TMN-8.

We propose a subspace based blind channel estimation method for orthogonal frequency-division multiplexing (OFDM) systems over a time-dispersive channel. Our approach is motivated by the resemblance of the multichannel signal model resulting from oversampling (or use of multiple receive sensors) of the received OFDM signal to that in conventional single carrier system. The proposed algorithm distinguishes itself from many previously reported channel estimation methods by the elimination of the cyclic prefix, thereby leading to higher channel utilization. Comparison of the proposed method with other two reported subspace channel estimation methods is presented by computer simulations to support its effectiveness.

In this paper, a new subspace based blind channel estimation method is proposed for OFDM systems over a time-dispersive channel. The proposed algorithm exploits the presence of virtual carriers and eliminates the cyclic prefix; thereby leading to higher channel utilization than most previously reported cyclic prefix based estimators. A sufficient condition on the channel identifiability is developed. Comparison with two other cyclic prefix based subspace methods is presented via computer simulations to support the effectiveness of the proposed method.

A new frequency domain approach towards blind channel identification for multirate communication systems is described. Users are first separated based on different cyclic frequencies corresponding to their respective symbol rates, thereby resulting in a single-user (blind) identification scenario. The algorithm proposed by L. Tong et al. (see IEEE Trans. Inform. Theory, vol.41, no.1 p.329-34, 1995) is then used to estimate the channels for each rate. Computer simulations demonstrate the effectiveness of our method.

The problem of blind channel identification for multirate, multiuser communication systems is addressed. By exploiting symbol rate differences, it is shown that users can be separated based on the autocorrelation of the received signal, thus reducing the problem to the familiar single rate setting. A subspace method is then developed to identify the channel associated with each user. Simulations are used to explore algorithm performance as a function of key factors such as signal-to-noise ratio (SNR) and signal-to-interference ratio (SIR).

We propose a subspace based blind channel estimation method for OFDM systems over a time-dispersive channel. Our approach is motivated by the resemblance of the multichannel signal model resulting from oversampling (or use of multiple receive sensors) of the received OFDM signal to that in a conventional single carrier system (Moulines et al. 1995). The proposed algorithm distinguishes itself from many previously reported channel estimation methods by the elimination of the cyclic prefix (CP), thereby leading to higher channel utilization. Comparison of the proposed method with other two reported subspace channel estimation methods (Heath and Giannakis 1999; Xiaodong Cai and Akansu 2000) is presented by computer simulations to support its effectiveness.

An analytical framework for multiple TCP flows sharing a bottleneck link under the random early detection (RED) regime is developed. Closed form expressions for the steady state throughput and average queueing delay are derived and verified by simulations; these show that RED significantly improves the inherent TCP bias against links with higher round-trip delays as compared to tail drop, contrary to prevailing belief. Further, we derive closed form bounds on the minimum average queuing delay achievable through a RED gateway with no deterministic packet drop.

In this paper, we propose a unified approach to blindly identify channels for multirate CDMA systems-both multiple code (MC) and variable processing gain (VPG) systems are considered. A time-domain subspace approach to blind channel estimation introduced in Torlak and Xu (1997) is generalized to the multi-rate case. Performance evaluation is conducted based on the normalized root mean square error (NRMSE) with an appropriate single-rate as a baseline for comparison.

An analytical framework for modeling the performance of a single TCP session in the presence of random packet loss is presented. A Markovian approach is developed that allows us to study both memoryless channels (IID packet loss) and channels with memory (correlated packet loss) modeled by a two-state continuous-time Gilbert model. The analytical results are validated against results using the ns simulator. It is shown that the model predicts throughput for LAN/WAN (low and high bandwidth-delay products) with good accuracy. Further, throughput for the IID loss model is found to be relatively insensitive to the probability density function (PDF) of the loss inter-arrival process. For channels with memory, we present an empirically validated rule of thumb to categorize the channel transition frequency.

Direct adaptive realizations of the linear minimum mean-square error (MMSE) receiver for direct-sequence code-division multiple access possess the attractive feature of not requiring any explicit information of interference parameters such as timing, amplitudes, or spreading sequences; however, they need a training sequence for the desired user. Previously, a new blind adaptive receiver was proposed based on an anchored least mean-squared (LMS) algorithm that requires only the spreading code and symbol timing of the desired user but obviates the need for a training sequence. In this work, it is analytically demonstrated that the blind LMS algorithm always provides (nominally) faster convergence than the training driven LMS-MMSE receiver of but at the cost of increased tap-weight fluctuations or misadjustment. Second, the property that the optimal MMSE or minimum-output energy filter coefficients lies in the signal subspace is exploited to propose a new efficient blind adaptive receiver requiring fewer adaptive coefficients. Improved detector characteristics (superior convergence rates and steady-state signal-to-interference-plus-noise ratios) is indicated by analysis and supported by simulation.

In this paper, receiver design and performance analysis for coded asynchronous code-division multiple access (CDMA) systems is considered. The receiver front-end consists of the near-far resistant multiuser detector known as the projection receiver (PR). The PR performs multiple-access interference resolution and is followed by error-control decoding. The output of the projection receiver yields the appropriate metric (i.e., soft information) for decoding of the coded sequences. An expression for the metric is derived that allows the use of a standard sequence decoder (e.g., Viterbi algorithm, M-algorithm) for the error-control code. It is then shown that the metric computer has an elegant adaptive implementation based on an extension of the familiar recursive least squares (RLS) algorithm. The adaptive PR operates on a single sample per chip and achieves a performance virtually identical to the algebraic PR, but with significantly less complexity. The receiver performance is studied for CDMA systems with fixed and random spreading sequences, and theoretical performance degradations with regard to the single-user bound are derived. The near-far resistance of the PR is also proven, and demonstrated by simulation.

A new multiuser receiver for synchronous code-division multiple-access (CDMA) systems with error control coding is proposed. The receiver achieves interference cancellation by projecting the undesired users onto the space spanned by the desired users' signal vectors. The detector calculates the least squares (LS) estimate of the interfering users data, that is used to yield an adjusted metric for maximum likelihood sequence estimation (MLSE) for the desired users' sequences. Simulation results indicate that close to optimal performance can be achieved when all but one of the users are projected using only a single user decoder for the desired user. Further, an adaptive receiver structure based on the recursive LS update is presented that is well-suited for DSP implementation due to it's computational efficiency.

Channel coding for an impulse noise environment modeled as a Cauchy-Gaussian mixture is addressed. Code design based on the pairwise probability of error indicates the suitability of Hamming distance as a primary determinant of performance. Simulation results of code performance for the maximum likelihood (ML) and several suboptimal metrics are presented.

Cutoff rates for (perfect) coordinate interleaving over flat Rayleigh fading channels are computed for some representative two-dimensional (2-D) and four-dimensional (4-D) quadrature amplitude modulation (QAM) schemes and compared to the standard symbol interleaved approaches. It is shown that for optimized coordinate interleaving [i.e., using optimum rotation parameters that maximize the cutoff rate for a given signal-to-noise ratio (SNR)], coding gains can be achieved vis-a-vis symbol interleaving that increases with the dimensionality of the signal constellation. Perfect coherent detection, as well as perfect channel state information are assumed.

A joint transmitter/receiver optimization problem for multiuser communications in a symmetric crosstalk environment based on the minimum mean squared error (MMSE) criterion is addressed. It is assumed that each user employs an identical transmit pulse shaping filter and sees identical direct and crosstalk channel responses. All the channels are assumed to be bandlimited with identical support that, in general, extends beyond the basic Nyquist zone [-(1/2T), 1/2T], corresponding to the common symbol period T. Necessary conditions for the optimum transmitter and receiver are derived and several useful insights generated. In particular, the performance advantage obtained by exploitation of the cyclostationary nature of the interference is demonstrated, corroborating earlier results. An algorithmic procedure to solve for the jointly optimal transmit-receive pair is outlined and used for numerical evaluation of the system performance as a function of several parameters of interest such as system bandwidth, the number of users and the number of points at which the transmitter is nonzero in the set (f: f/sub 0/+k/T) where T is the symbol period, and f/sub 0/ /spl isin/[-(1/2T),1/2T].

The application of importance sampling (E)to the problem of detecting random signals is considered. It is well known that conventional importance sampling (CIS) which uses a scaled IS density suffers from a dimensionality effect when it is used to simulate systems that detect a known signal in additive noise. Our fundamental result shows that CIS is guaranteed to give an IS gain when used to simulate the detection-of-scale problem. Further, a numerical example for the generalized Gaussian family is provided where the IS gain from CIS actually increases with the dimensionality of the problem.

Two dimensional, separable signal models are proposed for modeling the effects of intersymbol and inter-track interference in high-density magnetic storage media. The optimum (minimum mean-squared error) linear and decision feedback equalizers based on these models are developed. The use of a two dimensional LMS algorithm for adaptive updating of the equalizer coefficients is discussed and analytical results presented. Finally, simulation evidence is provided to predict the performance improvements achievable based on these models vis-a-vis one dimensional equalization.>

The problem of joint transmitter and receiver optimization for MIMO systems under the mean-squared error (MSE) criterion is revisited. We address the general problem of N (number of users) /spl ne/M (number of channel inputs) /spl ne/P (number of channel outputs) when the system is Nyquist bandlimited and obtain analytical solutions for the optimal transmit-receive pair. Next, we demonstrate how the above result is directly applicable to the problem where the system has excess bandwidth, thereby generalizing the results of Salz (1985). In conclusion, several numerical examples are included to demonstrate the performance gains obtainable with jointly optimized MIMO systems vis-a-vis systems based only on receiver optimization.>

The problem of echo cancellation in a multitone modulation (MTM) scheme is addressed. A general model for the near-end echo is derived and is used to identify candidate data-driven echo canceller (DDEC) structures. The stability, steady state performance, and associated system complexity of an adaptive DDEC based on the stochastic gradient approach is developed. It is further shown how the symmetry in the derived echo path model can be exploited to enable a reduction in canceller complexity, enhancing convergence speed without sacrificing final SNR. Simulation results are provided that confirm the analytical predictions.>

The joint transmit-receive optimization problem for multiuser communication systems with decision feedback is investigated. It is shown that minimization of the geometric mean-squared error (defined as the determinant of the error covariance matrix) leads to a tractable transmitter optimization problem for general multi-input multi-output decision-feedback systems. Several computational results are included that highlight system performance for a variety of useful transmission scenarios.>

Parametric adaptive importance sampling (IS) algorithms that adapt the IS density to the system of interest during the course of the simulation are discussed. This approach removes the burden of selecting the IS density from the system designer. The performance of two such algorithms is investigated for both linear and nonlinear systems operating in Gaussian noise. In addition, the algorithms are shown to converge to the optimum improved importance sampling density for the special case of a linear system with Gaussian noise.>