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In this paper, we consider the precoder design for an underloaded or critically loaded downlink multi-user multiple-input multiple-output (MIMO) communication system. We propose novel precoding and decoding schemes which enhance system performance based on rate splitting at the transmitter and single-stage successive interference cancellation at the receivers. The proposed successive null-space (SNS) precoding utilizes linear combinations of the null-space basis vectors of the successively augmented MIMO channel matrices of the users as precoding vectors to adjust the inter-user-interference experienced by the receivers. We formulate a non-convex weighted sum rate optimization problem for the precoding vectors and the associated power allocation for the proposed SNS-based MIMO-rate-splitting multiple access (RSMA) scheme. We obtain a suboptimal solution for this problem via successive convex approximation. Moreover, we study the robustness of the proposed precoding scheme to imperfect channel state information (CSI) at the base station via derivative-based sensitivity analysis. Our analysis and simulation results reveal the enhanced performance and robustness of the proposed SNS-based MIMO-RSMA scheme over several baseline multi-user MIMO schemes, especially for imperfect CSI. [ABSTRACT FROM AUTHOR]

Federated learning (FL) has recently emerged as a promising technology to enable artificial intelligence (AI) at the network edge, where distributed mobile devices collaboratively train a shared AI model under the coordination of an edge server. To significantly improve the communication efficiency of FL, over-the-air computation allows a large number of mobile devices to concurrently upload their local models by exploiting the superposition property of wireless multi-access channels. Due to wireless channel fading, the model aggregation error at the edge server is dominated by the weakest channel among all devices, causing severe straggler issues. In this paper, we propose a relay-assisted cooperative FL scheme to effectively address the straggler issue. In particular, we deploy multiple half-duplex relays to cooperatively assist the devices in uploading the local model updates to the edge server. The nature of the over-the-air computation poses system objectives and constraints that are distinct from those in traditional relay communication systems. Moreover, the strong coupling between the design variables renders the optimization of such a system challenging. To tackle the issue, we propose an alternating-optimization-based algorithm to optimize the transceiver and relay operation with low complexity. Then, we analyze the model aggregation error in a single-relay case and show that our relay-assisted scheme achieves a smaller error than the one without relays provided that the relay transmit power and the relay channel gains are sufficiently large. The analysis provides critical insights on relay deployment in the implementation of cooperative FL. Extensive numerical results show that our design achieves faster convergence compared with state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

Fluid antenna system represents an emerging technology that enables an antenna to switch its physical location in a predefined space. This paper explores the potential of using a single fluid antenna at each mobile user for multiple access, which we refer to it as fluid antenna multiple access (FAMA). FAMA exploits spatial moments of deep fade suffered by the interference to achieve a favourable channel condition for the desired signal, without requiring sophisticated signal processing. We analyze the FAMA network by first deriving the outage probability of the signal-to-interference ratio (SIR) in a double integral form. We then obtain an outage probability upper bound in closed form and an average outage rate lower bound for the FAMA system, with an arbitrary number of interferers, from which the multiplexing gain of FAMA is characterized. We also estimate how large the number of locations is required to achieve a given multiplexing gain using fluid antennas with a given size. Results show that it is possible for FAMA to support hundreds of users using only one fluid antenna of a few wavelengths of space at each user, giving rise to significant gain in the average network outage rate. [ABSTRACT FROM AUTHOR]

To support massive connectivity for sporadically active devices is a challenging task, as the randomness of the channel and the large number of users lead to enormous increase of communication overhead. Different to the existing methods that differentiate users in resources including time, frequency and code, we propose a new joint activity detection and channel estimation framework for massive multiple-input multiple-output (MIMO) systems, where angular domain information of active users is exploited to enhance activity detection and channel estimation. By exploiting the sporadic activity of users and the angular spread of the wireless signals, the activity detection and channel estimation is formulated as a compressive sensing problem with multiple measurement vectors, which has a simultaneously row-sparse and clustered sparse structure. The sizes and positions of the nonzero clusters are arbitrary, which brings new challenges for algorithm derivation. To this end, we develop new algorithms based on sparse Bayesian learning, where novel hyper-priors are proposed to capture the structural signal characteristics, and appropriate approximations are employed to facilitate algorithm derivations. Numerical experiments demonstrate the improved activity detection and channel estimation performance of the proposed approach in comparison to the existing methods. [ABSTRACT FROM AUTHOR]

Multiple-access edge computation offloading (MECO) systems have been highlighted as a solution for extending the battery life and computation capability of mobile devices. However, in scenarios where information data and computation offloading (CO) data coexist, CO users and information users affect each other. It means that the communication resources for information data transmission are inevitably reduced by the communication resources allocated for CO in the conventional half-duplex (HD) based systems. Hence, improving the spectral efficiency of MECO systems in coexistence scenarios is essential, and we investigate a full-duplex (FD)-aided MECO (FD-MECO) system. A step-wise resource configuration is proposed to improve the performance of computation offloading under the information data rate constraint. The main idea is to improve spectral efficiency by maximizing the opportunity of operating in FD mode. By comparing all the communication phases in FD-MECO systems, the proposed resource configuration maximizes the amount of delivered CO data while guaranteeing the required information data rate. The simulation results show that FD-MECO systems with the proposed resource configuration always outperform HD-MECO systems. [ABSTRACT FROM AUTHOR]

To exploit massive amounts of data generated at mobile edge networks, federated learning (FL) has been proposed as an attractive substitute for centralized machine learning (ML). By collaboratively training a shared learning model at edge devices, FL avoids direct data transmission and thus overcomes high communication latency and privacy issues as compared to centralized ML. To improve the communication efficiency in FL model aggregation, over-the-air computation has been introduced to support a large number of simultaneous local model uploading by exploiting the inherent superposition property of wireless channels. However, due to the heterogeneity of communication capacities among edge devices, over-the-air FL suffers from the straggler issue in which the device with the weakest channel acts as a bottleneck of the model aggregation performance. This issue can be alleviated by device selection to some extent, but the latter still suffers from a tradeoff between data exploitation and model communication. In this paper, we leverage the reconfigurable intelligent surface (RIS) technology to relieve the straggler issue in over-the-air FL. Specifically, we develop a learning analysis framework to quantitatively characterize the impact of device selection and model aggregation error on the convergence of over-the-air FL. Then, we formulate a unified communication-learning optimization problem to jointly optimize device selection, over-the-air transceiver design, and RIS configuration. Numerical experiments show that the proposed design achieves substantial learning accuracy improvement compared with the state-of-the-art approaches, especially when channel conditions vary dramatically across edge devices. [ABSTRACT FROM AUTHOR]

Symbiotic radio (SR) is a new paradigm of spectrum sharing that allows passive Internet-of-Things (IoT) device to transmit messages over the ambient RF signal. Considering that the reader needs to collect information from multiple IoT devices in practice, and the traditional multiple access schemes that require coordination among users are unaffordable for the passive devices, we propose a random code assisted multiple access scheme, in which each backscatter device (BD) independently chooses a random code to spread its signal and the incident signal is backscattered. To avoid the need of the instantaneous information, including the specific codes and the instantaneous channel state information of the backscatter links, and to optimize the transmit power and the BD reflection coefficients, we derive the asymptotic BD signal to interference plus noise ratio (SINR) by employing the large-dimension random matrix theory. We formulate the joint optimization problem to maximize the minimum asymptotic SINR among BDs with guaranteeing the primary target rate. By investigating the property of the problem, the original problem is transformed and solved by the proposed iterative-based algorithm. Extensive simulations are executed to verify our theoretical analysis and demonstrate the outperformance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Over-the-air computation (AirComp) of a function (e.g., averaging) has recently emerged as an efficient multiple-access scheme for fast aggregation of distributed data at mobile devices (e.g., sensors) at a fusion center (FC) over wireless channels. To realize reliable AirComp in practice, it is crucial to adaptively control the devices’ transmit power for coping with channel distortion to achieve the desired magnitude alignment of simultaneous signals. In this paper, we solve the power control problem. Our objective is to minimize the computation error by jointly optimizing the transmit power at devices and a signal scaling factor (called denoising factor) at the FC, subject to individual average power constraints at devices. The problem is generally non-convex due to the coupling of the transmit powers at devices and denoising factor at the FC. To tackle the challenge, we first consider the special case with static channels, for which we derive the optimal solution in closed form. The derived power control exhibits a threshold-based structure: if the product of the channel quality and power budget for each device, called quality indicator, exceeds an optimized threshold, this device applies channel-inversion power control; otherwise, it performs full power transmission. We proceed to consider the general case with time-varying channels. To solve the more challenging non-convex power control problem, we use the Lagrange-duality method via exploiting its “time-sharing” property. The derived power control exhibits a regularized channel inversion structure, where the regularization balances the tradeoff between the signal-magnitude alignment and noise suppression. Moreover, for the special case with only one device being power limited, we show that the power control for the power-limited device has an interesting channel-inversion water-filling structure, while those for other devices (with sufficiently large power budgets) reduce to channel-inversion power control. Numerical results show that the derived power control significantly reduces the computation error as compared with the conventional designs. [ABSTRACT FROM AUTHOR]

Interleaved Frequency Division Multiple Access (IFDMA) and Orthogonal FDMA (OFDMA) belong to a class of signal modulation and multiple-access techniques in which information of multiple users are multiplexed and carried on subcarriers within a shared spectrum. Compared with OFDMA, IFDMA has lower Peak-to-Average Power Ratio (PAPR). However, IFDMA poses two rigid constraints on subcarrier allocation: 1) the subcarriers occupied by a user must be evenly-spaced among the available subcarriers. 2) the number of subcarriers used by a user must be a divisor of the total number of subcarriers. Unless these constraints can be overcome, IFDMA may remain impractical despite its excellent PAPR. This paper investigates how to overcome these constraints to allow flexible and fine-grained subcarrier allocation in IFDMA. Specifically, we put forth $i$) a bit-reversal subcarrier allocation scheme whereby the problem of allocating evenly-spaced subcarriers is transformed to a more intuitive problem of filling contiguous bins; $ii$) a multi-stream IFDMA scheme whereby a user can have an arbitrary number of subcarriers. For the synchronous scenario in which user requests arrive in a synchronous manner, we show that IFDMA can achieve the same level of flexibility and granularity as OFDMA in subcarrier allocation. For the asynchronous scenario in which user requests arrive and depart asynchronously, we show that the blocking probability of IFDMA is only slightly worse than that of OFDMA: specifically, the gap between the blocking probabilities of IFDMA and OFDMA is only 2.56% at a moderate offered load. [ABSTRACT FROM AUTHOR]

We consider the non-coherent single-input multiple-output (SIMO) multiple access channel with general signaling under spatially correlated Rayleigh block fading. We propose a novel soft-output multi-user detector that computes an approximate marginal posterior of each transmitted signal using only the knowledge about the channel distribution. Our detector is based on expectation propagation (EP) approximate inference and has polynomial complexity in the number of users, number of receive antennas and channel coherence time. We also propose two simplifications of this detector with reduced complexity. With Grassmannian signaling, the proposed detectors outperform a state-of-the-art non-coherent detector with projection-based interference mitigation. With pilot-assisted signaling, the EP detector outperforms, in terms of symbol error rate, some conventional coherent pilot-based detectors, including a sphere decoder and a joint channel estimation–data detection scheme. Our EP-based detectors produce accurate approximates of the true posterior leading to high achievable sum-rates. The gains of these detectors are further observed in terms of the bit error rate when using their soft outputs for a turbo channel decoder. [ABSTRACT FROM AUTHOR]

Communication over the i.i.d. Rayleigh slow-fading MAC is considered, where all terminals are equipped with a single antenna. Further, a communication protocol is considered where all users transmit at (just below) the symmetric capacity (per user) of the channel, a rate which is fed back (dictated) to the users by the base station. Tight bounds are established on the distribution of the rate attained by the protocol. In particular, these bounds characterize the probability that the dominant face of the MAC capacity region contains a symmetric rate point, i.e., that the considered protocol strictly attains the sum capacity of the channel. The analysis provides a non-asymptotic counterpart to the diversity-multiplexing tradeoff of the multiple access channel. We then extend this analysis to general multiple-input multiple-output MAC and finally, a practical scheme based on integer-forcing and space-time precoding is shown to be an effective coding architecture for this communication scenario. [ABSTRACT FROM AUTHOR]

In this paper, an impartial simultaneous wireless information and power transfer (SWIPT)-assisted cooperation mechanism is proposed for a non-orthogonal multiple access (NOMA) downlink scenario. The key idea of the proposed impartial user cooperation mechanism (IUCM) is that not only the cell-center user but also the cell-edge user applies the power-splitting architecture and utilizes the harvested energy to forward the other user’s information. Analytical results show that the proposed IUCM outperforms the traditional partial cooperation mechanism in terms of outage probability, diversity order and diversity-multiplexing trade-off (DMT). For comparison, the proposed IUCM is further incorporated into an orthogonal frequency-division multiple access (OFDMA) framework, which is shown to preserve the same diversity order, while has a worse but more flexible DMT performance compared with the IUCM in the NOMA framework. Furthermore, a classic non-linear energy harvesting model is introduced, based on which the outage probability, diversity order and DMT performance of the proposed IUCM and the conventional mechanism are analyzed. Finally, representative numerical results are given to validate our theoretical analysis. [ABSTRACT FROM AUTHOR]

We design a Blind Network-Assisted Diversity Multiple Access (BNDMA) method for resolving packet collisions in synchronous packet-switched networks. As opposed to typical BNDMA schemes, the method operates in non-blocking mode. Idle transmitters at the start of a collision resolution interval may join the set of active transmitters and contact the receiver before the end of the interval. A naive queuing analysis of the proposed scheme is exponentially complex in the size of the network. We carry out a computationally efficient analysis of the network throughput and queuing delay. We show that the suggested scheme reduces the queuing delay of the buffered packets at the transmitters without sacrificing the maximum throughput achieved by standard BNDMA. Further insights are derived from the numerical experiments. [ABSTRACT FROM AUTHOR]

To leverage rich data distributed at the network edge, a new machine-learning paradigm, called edge learning, has emerged where learning algorithms are deployed at the edge for providing intelligent services to mobile users. While computing speeds are advancing rapidly, the communication latency is becoming the bottleneck of fast edge learning. To address this issue, this work is focused on designing a low-latency multi-access scheme for edge learning. To this end, we consider a popular privacy-preserving framework, federated edge learning (FEEL), where a global AI-model at an edge-server is updated by aggregating (averaging) local models trained at edge devices. It is proposed that the updates simultaneously transmitted by devices over broadband channels should be analog aggregated “over-the-air” by exploiting the waveform-superposition property of a multi-access channel. Such broadband analog aggregation (BAA) results in dramatical communication-latency reduction compared with the conventional orthogonal access (i.e., OFDMA). In this work, the effects of BAA on learning performance are quantified targeting a single-cell random network. First, we derive two tradeoffs between communication-and-learning metrics, which are useful for network planning and optimization. The power control (“truncated channel inversion”) required for BAA results in a tradeoff between the update-reliability [as measured by the receive signal-to-noise ratio (SNR)] and the expected update-truncation ratio. Consider the scheduling of cell-interior devices to constrain path loss. This gives rise to the other tradeoff between the receive SNR and fraction of data exploited in learning. Next, the latency-reduction ratio of the proposed BAA with respect to the traditional OFDMA scheme is proved to scale almost linearly with the device population. Experiments based on a neural network and a real dataset are conducted for corroborating the theoretical results. [ABSTRACT FROM AUTHOR]

In this work, we consider a sparse code multiple access uplink system, where $J$ users simultaneously transmit data over $K$ subcarriers, such that $J > K$ , with a constraint on the power transmitted by each user. To jointly optimize the subcarrier assignment and the transmitted power per subcarrier, two new iterative algorithms are proposed, the first one aims to maximize the sum-rate (Max-SR) of the network, while the second aims to maximize the fairness (Max-Min). In both cases, the optimization problem is of the mixed-integer nonlinear programming (MINLP) type, with non-convex objective functions, which are generally not tractable. We prove that both joint allocation problems are NP-hard. To address these issues, we employ a variant of the block successive upper-bound minimization (BSUM) framework, obtaining polynomial-time approximation algorithms to the original problem. Moreover, we evaluate the algorithms’ robustness against outdated channel state information (CSI), present an analysis of the convergence of the algorithms, and a comparison of the sum-rate and Jain’s fairness index of the novel algorithms with three other algorithms proposed in the literature. The Max-SR algorithm outperforms the others in the sum-rate sense, while the Max-Min outperforms them in the fairness sense. [ABSTRACT FROM AUTHOR]

Next-generation wireless networks will provide users ubiquitous low-latency computing services using devices at the network edge, called mobile edge computing (MEC). The key operation of MEC is to offload computation intensive tasks from users. Since each edge device comprises an access point (AP) and a computer server (CS), an MEC network can be decomposed as a radio access network cascaded with a CS network. Based on the architecture, we investigate network-constrained latency performance, namely communication latency and computation latency, under the constraints of radio-access connectivity and CS stability. To this end, a spatial random network is modeled featuring random node distribution, parallel computing, non-orthogonal multiple access, and random computation-task generation. Given the model and the said network constraints, we derive the scaling laws of communication latency and computation latency with respect to network-load parameters (density of mobiles and their task-generation rates) and network-resource parameters (bandwidth, density of APs/CSs, and CS computation rate). Essentially, the analysis involves the interplay of the theories of stochastic geometry, queueing, and parallel computing. Combining the derived scaling laws quantifies the tradeoffs between the latencies, network connectivity, and network stability. The results provide useful guidelines for MEC-network provisioning and planning by avoiding either of the cascaded radio access network or CS network being a performance bottleneck. [ABSTRACT FROM AUTHOR]

User pairing in non-orthogonal multiple-access (NOMA) uplink is investigated considering some predefined power allocation schemes. The base station divides the set of users into disjunct pairs and assigns the available resources to these pairs. The combinatorial problem of user pairing to achieve the maximum sum rate is analyzed in the large system limit for various scenarios, and some optimum and sub-optimum algorithms with a polynomial-time complexity are proposed. In the first scenario, $2~M$ users and the base station have a single-antenna and communicate over $M$ subcarriers. The performance of optimum pairing is derived for $M\rightarrow \infty $ and shown to be superior to random pairing and orthogonal multiple access techniques. In the second setting, a novel NOMA scheme for a multi-antenna base station and single carrier communication is proposed. In this case, the users need not be aware of the pairing strategy. Furthermore, the proposed NOMA scheme is generalized to multi-antenna users. It is shown that for the considered power allocation scheme, random and optimum user pairing perform similarly in the large system limit, but optimum pairing is significantly better in finite dimensions. It is shown that NOMA with the proposed user pairing scheme outperforms a previously proposed NOMA with signal alignment. [ABSTRACT FROM PUBLISHER]

The feasibility of practical in-band full-duplex radios has recently been demonstrated experimentally. One way to leverage full-duplex in a network setting is to enable three-node full-duplex, where a full-duplex access point (AP) transmits data to one node yet simultaneously receives data from another node. Such three-node full-duplex communication, however, introduces inter-client interference, directly impacting the full-duplex gain. It hence may not always be beneficial to enable three-node full-duplex transmissions. In this paper, we present a distributed full-duplex medium access control (MAC) protocol that allows an AP to adaptively switch between full-duplex and half-duplex modes. We formulate a model that determines the probabilities of full-duplex and half-duplex access so as to maximize the expected network throughput. A MAC protocol is further proposed to enable the AP and clients to contend for either full-duplex or half-duplex transmissions based on their assigned probabilities in a distributed way. Our evaluation shows that, by combining the advantages of centralized probabilistic scheduling and distributed random access, our design improves the overall throughput by 1.53 times, on average, as compared with the greedy downlink-uplink client pairing. [ABSTRACT FROM PUBLISHER]

We introduce a novel scheme to perform radio frequency identification (RFID) with compressed sensing techniques. The proposed scheme allows quick and reliable identification of several RFID tags, even at low signal-to-noise ratio. Contrary to the widely used frame slotted ALOHA (FSA) protocol, the tags activated by a reader deliberately respond simultaneously with their assigned signature during the acquisition phase; collisions are regarded as beneficial rather than destructive. The signatures are drawn from a huge signature pool, and the set of signatures that is assigned to the activated tags is very small compared to the total signature count. This introduces sparsity to the acquisition phase which, in turn, allows formulation of the acquisition as a compressed sensing measurement. Furthermore, our formulation permits the usage of a low-complexity approximate message passing algorithm for compressed sensing recovery. We compare two realizations of the compressed sensing-based approach to the FSA protocol. The first performs fixed signature assignment—this enables very quick identification but sacrifices flexibility. The second performs random signature assignment—this reduces the identification speed but provides flexibility. A comparison via simulation shows that both compressed sensing-based approaches significantly outperform FSA in terms of identification speed and robustness to noise. [ABSTRACT FROM PUBLISHER]

The effect of full-duplex cooperative relaying in a random access multiuser network is investigated here. First, we model the self-interference incurred due to full-duplex operation, assuming multi-packet reception capabilities for both the relay and the destination node. Traffic at the source nodes is considered saturated and the cooperative relay, which does not have packets of its own, stores a source packet that it receives successfully in its queue when the transmission to the destination has failed. We obtain analytical expressions for key performance metrics at the relay, such as arrival and service rates, stability conditions, and average queue length, as functions of the transmission probabilities, the self interference coefficient, and the links' outage probabilities. Furthermore, we study the impact of the relay node and the self-interference coefficient on the per-user and aggregate throughput, and the average delay per packet. We show that perfect self-interference cancelation plays a crucial role when the SINR threshold is small, since it may result to worse performance in throughput and delay comparing with the half-duplex case. This is because perfect self-interference cancelation can cause an unstable queue at the relay under some conditions. [ABSTRACT FROM PUBLISHER]

We study from a cross-layer perspective a cognitive network consisting of one primary user (PU) and one secondary user (SU). In contrast with the oversimplified collision channel model, we assume that simultaneous PU and SU transmissions are successful with some positive probability. We propose and analyze two access schemes at the SU aiming at maximizing its stable throughput while guaranteeing the stability of the PU's queue. These schemes exploit the SU's knowledge of the channel statistics and of the average arrival rate to the PU. In the first scheme, the SU accesses the channel at all slots with fixed probability p^* without sensing. In the second scheme, the SU accesses the channel with probabilities p_1^* and p_2^* when the PU is sensed to be idle and busy, respectively. The analysis shows that if simultaneous PU and SU transmissions are likely to be successful, schemes with no sensing outperform schemes with sensing. Otherwise, schemes with sensing are preferred. Therefore, using complex receivers capable of handling interference, alleviates the need of complex SU transmitters with strong sensing capabilities. We then extend the analysis to the case where the PU has an average delay constraint which is more restrictive than the stability constraint. [ABSTRACT FROM PUBLISHER]

This paper considers the application of compressed sensing (CS) to a wireless sensor network for data measurement communication and reconstruction, where N sensor nodes compete for medium access to a single receiver. Sparsity of the sensor data in three domains due to time correlation, space correlation and multiple access are being utilized. We first provide an in-depth analysis on the CS-based medium access control schemes from a physical layer perspective and reveal the impact of communication signal-to-noise ratio on the reconstruction performance. We show the process of the sensor data converted to the modulated symbols for physical layer transmission and how the modulated symbols being recovered via compressed sensing. This paper further identifies the decision problem of distinguishing between active and inactive transmitters after symbol recovery and shows a comprehensive performance comparison between carrier sense multiple access and the proposed CS-based scheme. Second, a network data recovery scheme that exploits both spatial and temporal correlations is proposed. Simulation results validate the effectiveness of the proposed method in terms of communication throughput and show that enhanced performance can be obtained by utilizing the sensed signal's temporal and spatial correlations. [ABSTRACT FROM PUBLISHER]

Network coding has been widely used in wireless uplink to improve spectral efficiency. However, the relay decoding error may propagate to the intended receiver and thus severely degrade the diversity performance. So in this work, we develop two power scaling schemes at the relay side and two detection schemes at the receiver side, respectively, to mitigate error propagation and thus achieve full diversity for the two-user multiple access relay network. For the soft power scaling based link adaptive relaying, we develop a virtual source-relay-destination channel model and demonstrate that the relay power should be such to balance the signal-to-noise ratios of the source-relay channel and relay-destination channel. As for the hard power scaling based ON-OFF relaying, we first design a decision rule based on total pairwise error probability, and then simplify it to the threshold-based relaying strategy. At the receiver side, we show that the weighted minimum distance detection with the weight being determined by the relative link quality of source-relay channel and relay-destination channel can achieve full diversity once the global channel state information is available, otherwise the maximum likelihood detection should be employed to achieve full diversity when the receiver only knows the local channel state information. [ABSTRACT FROM PUBLISHER]

Rapid and reliable timing synchronization is a demanding task in the receiver design for ultra-wideband (UWB) communication systems, especially when concurrent multiple access is called for. This paper derives a maximum likelihood based timing synchronization scheme for UWB multiple access. Relying on a set of user-specific training sequences, the novel concept of weighted average template is introduced, leading to a multiple access timing synchronizer that works in the absence of any channel knowledge and is resilient to both multiple access interference and noise. Simulation runs testify the effectiveness of the proposed scheme in terms of mean square timing estimation errors and bit-error-rate detection performance when operating in multiple access and dense multipath scenarios. [ABSTRACT FROM PUBLISHER]

A novel high data rate (HDR) Prerake DS UWB multiple access system is proposed, in which the number of taps in the Prerake filter is set to a large value while keeping the number of taps in a chip sufficiently small. Thus high data rate can be achieved via superposition of the chip waveforms, where the inter-chip interference introduced is small due to signal energy focusing. We derive the higher order moments of Multiple Access Interference (MAI) and fit the distribution of MAI using a generalized Gaussian distribution. Numerical results show that the generalized Gaussian distribution is a more appropriate statistical model for the distribution of MAI than the Gaussian distribution. Using the characteristic function (CF) method, an accurate BER formula is derived and validated by numerical results. The effect of imperfect channel estimation is discussed in detail. We highlight that under imperfect channel estimation, there is a tradeoff between the signal energy captured and the channel estimation noise introduced. [ABSTRACT FROM PUBLISHER]

In this paper, a cross-layer design framework for multi-input multi-output (MIMO)/orthogonal frequency division multiplexing (OFDM) based wireless local area networks (WLANs) is proposed. In contrast to conventional systems where the medium access control (MAC) and physical (PHY) layers are separately optimized, our proposed methodology jointly designs a multi-packet reception (MPR) based protocol with adaptive resource allocation. Specifically, a realistic collision model is employed by taking into consideration the PHY layer parameters such as channel information, space-time coded beamforming and multiuser detection, as well as sub-carrier, bit, and power allocation. The allocation problem is formulated, so as to maximize the system throughput, subject to the constraints from both the MAC and PHY layers. These constraints depend on the results of access contention, data packetsiquest length, usersiquest spatial correlation and the quality of channel feedback information. An iterative algorithm is then provided to obtain the optimal solution. Simulation results will show that our proposed approach achieves significant improvement in system performance such as average throughput and packet delay, compared with conventional schemes where cross-layer design and optimization is not used. [ABSTRACT FROM PUBLISHER]

In this paper, an innovative frequency domain joint estimation algorithm for synchronization parameter and channel impulse response (CIR) in direct sequence code division multiple access (DS-CDMA) systems is proposed. The algorithm is based on the expectation-maximization (EM) method. It can provide accurate estimation of channel state information and synchronization parameter for a DS-CDMA receiver even with a simple equalization module (e.g., an one-tap multiplier based frequency domain equalizer (FDE)), and a radio receiver with this approach performs better than a costly multi-tap multiplier based equalizer, such as the time domain equalizer (TDE). A generic receiver architecture based on the frequency domain equalization for a composite radio, which works in both CDMA and orthogonal frequency division multiplexing (OFDM) modes, is also proposed. The Cramer-Rao lower bound (CRLB) of the proposed estimator and its optimization scheme are derived. This architecture can be implemented with an iterative approach, and the results demonstrate that this adaptive receiver performs very well with a relatively low cost. [ABSTRACT FROM PUBLISHER]

This paper analyzes the power spectral density (PSD) characteristics of ultra wideband (UWB) signals modulated by M-ary code shift keying (MCSK) that can be combined with binary pulse position modulation (BPPM) and binary pulse amplitude modulation (BPAM), which we refer to as MCSK based impulse radios (IR). MCSK based IR are modified IR that were designed to increase the data rate of conventional IR by embedding the data on a time hopping (TH) code randomly selected from a set of M distinct TH codes per user. This random selection also results in increased effective TH code period, which- helps smoothing the continuous spectrum and suppressing the discrete spectral components. In combination with the random code selection, design of the TH code set for each user is very important for spectrum shaping and multiple access (MA) capability, and is addressed in detail in the paper. [ABSTRACT FROM PUBLISHER]

In this paper, we study the uplink of a cellular network where reservation random access schemes such as reservation slotted ALOHA and reservation slotted nonpersistent ISMA are used for multiple access. When channel state information is not available to users when they contend for channel access, we find that capture effect inherent in wireless communications can exploit the channel variations and reserve users with favorable channels for data transmission. We investigate two channel models where in the first model, channel variations come from time-varying Nakagami-m fading and in the second model, mobile users have both time-varying fading and path loss [ABSTRACT FROM PUBLISHER]

In integrated wireless multimedia service, isochronous traffic of different connections can be scheduled by using a most regular binary sequence (MRBS). Such a sequence schedules traffic in an evenly spaced manner to achieve any arbitrary rate asymptotically and while avoiding excessive delay or buffering requirement. Flexible slot assignment that can match requests exactly improves bandwidth efficiency in multirate operations. The most regular binary sequence provides a distributed solution for multiaccess control that is based on limited information exchange. As a generalization, the concept of a most regular code sequence (MRCS) is proposed to support variable rate transmission in wideband code division multiple access (CDMA) systems and to provide spreading factor (SF) optimization. This scheme improves channel utilization efficiency in supporting traffics of various classes and hence results in an overall capacity gain. [ABSTRACT FROM PUBLISHER]

We consider multiuser MIMO systems with some of the users having target-rate requirements while the other users are working on best-effort data transmission. Both multiple-access channels (MAC) and broadcast channels (BC) are considered. We show that the best-effort users can achieve higher rates when the data streams of any user are not restricted to be decoded consecutively and when time-sharing between different decoding orders is allowed. For MIMO-MAC, we show that the problem can be formulated as a convex optimization problem, and hence efficient algorithms can be used to obtain the globally optimal solution. We also show that in some cases it is possible to reduce the transmission power of some users without affecting the optimal solution, and we show that the power minimization problem is convex. We also exploit the MAC-BC duality in order to solve the same problem for the MIMO-BC channel. [ABSTRACT FROM PUBLISHER]

Spectrum sensing is an essential functionality of cognitive radio networks. However, the effect of errors in the spectrum sensing process on the performance of the multiple access layer of both primary and secondary networks has not gained much attention. This paper aims at bridging the gap between the study of spectrum sensing and the multiple access of cognitive radio networks. To achieve this goal we pose and answer the question how the spectrum sensing errors affects the performance of cognitive radio networks from a multiple access protocol design point of view. The negative effects of the spectrum sensing errors on the throughput of both primary and secondary networks are characterized through queuing theory analysis of both networks. To alleviate these negative effects a novel joint design of the spectrum sensing and channel access mechanisms is proposed. This design is based on the observation that, in a binary hypothesis testing problem, the value of the test statistics could be used as a confidence measure for the test outcome. Therefore, this value will be used to define different channel access probabilities for secondary users. Results reveal a significant performance improvement in the maximum stable throughput of both primary and secondary networks by virtue of the proposed technique. [ABSTRACT FROM PUBLISHER]

Spectrally precoded orthogonal frequency-division multiplexing with cyclic prefix (SP-CP-OFDM) and SP-CP-OFDM multiple access (SP-CP-OFDMA) are investigated in this paper. A general constraint on spectral precoding is developed for both SP-CP-OFDM and SP-CP-OFDMA signal formats with unconstrained guard ratios and arbitrary input data statistics to ensure very small power spectral sidelobes decaying asymptotically as f^-2J-2, with J a predesigned integer-valued parameter. In the SP-CP-OFDM signaling format, new spectral precoders are devised to meet the constraint. It is shown that the proposed SP-CP-OFDM signals can provide much smaller spectral sidelobes than the previously designed SP-CP-OFDM signals with block partitioning and constrained guard ratios. In the SP-CP-OFDMA signaling format, a general procedure is proposed to facilitate the precoder design for SP-CP-OFDMA signals with arbitrary subcarrier allocation for each user and some spectral precoders are accordingly devised. It is shown that the proposed SP-CP-OFDMA signals can suppress sidelobe powers effectively and thus achieve higher spectral compactness than nonprecoded rectangularly-pulsed CP-OFDMA. [ABSTRACT FROM PUBLISHER]

This paper aims to analyze the throughput of a multiple-input multiple-output (MIMO) multiple-access (MA) wireless network. Some recent research studies showed that, in the concerned scenario, the joint processing of all the received signals by access point (AP) cooperation can dramatically enhance the system throughput because of the macrodiversity. However, in practice, the channel estimation quality for the paths from the macrodiversity providers is usually poor. Unfortunately, existing literature on the performance of the joint processing in the MIMO cellular networks is deficient in channel estimation errors. To fill this literature gap, this paper provides an analytical framework for calculating the large-system throughput of a MIMO cellular network with channel estimation errors. Unlike most large-system results, analytical results of this study can be applied in the scenarios with any given input distributions (not necessarily Gaussian) from transmitters. In addition, several issues including 1) how much of the coherence interval should be spent on training and 2) the impact of AP cooperation are highlighted by the analytical results. [ABSTRACT FROM PUBLISHER]