Showing papers in "Eurasip Journal on Wireless Communications and Networking in 2008"
TL;DR: It is numerically show that the singularity problem can be eased by linear precoding techniques aided with multiuser selection, and the tradeoff between the performance improvement and the requirement for BS cooperation, signal processing complexity, and channel state information at the transmitter is shown.
Abstract: We study the potential benefits of base-station (BS) cooperation for downlink transmission in multicell networks. Based on a modified Wyner-type model with users clustered at the cell-edges, we analyze the dirty-paper-coding (DPC) precoder and several linear precoding schemes, including cophasing, zero-forcing (ZF), and MMSE precoders. For the nonfading scenario with random phases, we obtain analytical performance expressions for each scheme. In particular, we characterize the high signal-to-noise ratio (SNR) performance gap between the DPC and ZF precoders in large networks, which indicates a singularity problem in certain network settings. Moreover, we demonstrate that the MMSE precoder does not completely resolve the singularity problem. However, by incorporating path gain fading, we numerically show that the singularity problem can be eased by linear precoding techniques aided with multiuser selection. By extending our network model to include cell-interior users, we determine the capacity regions of the two classes of users for various cooperative strategies. In addition to an outer bound and a baseline scheme, we also consider several locally cooperative transmission approaches. The resulting capacity regions show the tradeoff between the performance improvement and the requirement for BS cooperation, signal processing complexity, and channel state information at the transmitter (CSIT).
271 citations
TL;DR: In this paper, the capacity region of a Gaussian state-dependent multi-access channel with one informed encoder was derived for the general discrete memoryless case and for the binary noiseless case, where one of the encoders has noncausal access to the channel state.
Abstract: We consider a state-dependent multiaccess channel (MAC) with state noncausally known to some encoders. For simplicity of exposition, we focus on a two-encoder model in which one of the encoders has noncausal access to the channel state. The results can in principle be extended to any number of encoders with a subset of them being informed. We derive an inner bound for the capacity region in the general discrete memoryless case and specialize to a binary noiseless case. In binary noiseless case, we compare the inner bounds with trivial outer bounds obtained by providing the channel state to the decoder. In the case of maximum entropy channel state, we obtain the capacity region for binary noiseless MAC with one informed encoder. For a Gaussian state-dependent MAC with one encoder being informed of the channel state, we present an inner bound by applying a slightly generalized dirty paper coding (GDPC) at the informed encoder and a trivial outer bound by providing channel state to the decoder also. In particular, if the channel input is negatively correlated with the channel state in the random coding distribution, then GDPC can be interpreted as partial state cancellation followed by standard dirty paper coding. The uninformed encoders benefit from the state cancellation in terms of achievable rates, however, it seems that GDPC cannot completely eliminate the effect of the channel state on the achievable rate region, in contrast to the case of all encoders being informed. In the case of infinite state variance, we provide an inner bound and also provide a nontrivial outer bound for this case which is better than the trivial outer bound.
96 citations
TL;DR: This paper works around potentially computational intractability; the proposed PSO scheme exploits heuristics to search the optimal combination of phase factors with low complexity, and results show that the new technique can effectively reduce the computation complexity and PAPR reduction.
Abstract: A suboptimal partial transmit sequence (PTS) based on particle swarm optimization (PSO) algorithm is presented for the low computation complexity and the reduction of the peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) system In general, PTS technique can improve the PAPR statistics of an OFDM system However, it will come with an exhaustive search over all combinations of allowed phase weighting factors and the search complexity increasing exponentially with the number of subblocks In this paper, we work around potentially computational intractability; the proposed PSO scheme exploits heuristics to search the optimal combination of phase factors with low complexity Simulation results show that the new technique can effectively reduce the computation complexity and PAPR reduction
78 citations
TL;DR: A thermal-aware routing algorithm, called least total-route-temperature (LTRT) protocol, in which nodes temperatures are converted into graph weights, and minimum temperature routes are obtained, is proposed.
Abstract: Biomedical sensors, called invivo sensors, are implanted in human bodies, and cause some harmful effects on surrounding body tissues. Particularly, temperature rise of the invivo sensors is dangerous for surrounding tissues, and a high temperature may damage them from a long term monitoring. In this paper, we propose a thermal-aware routing algorithm, called least total-route-temperature (LTRT) protocol, in which nodes temperatures are converted into graph weights, and minimum temperature routes are obtained. Furthermore, we provide an extensive simulation evaluation for comparing several other related schemes. Simulation results show the advantages of the proposed scheme.
75 citations
TL;DR: This paper presents adaptive predistortion techniques based on a feed-forward neural network to linearize power amplifiers such as those used in satellite communications and presents the suitable NN structures which give the best performances for three satellite down links.
Abstract: This paper presents adaptive predistortion techniques based on a feed-forward neural network (NN) to linearize power amplifiers such as those used in satellite communications. Indeed, it presents the suitable NN structures which give the best performances for three satellite down links. The first link is a stationary memoryless travelling wave tube amplifier (TWTA), the second one is a nonstationary memoryless TWT amplifier while the third is an amplifier with memory modeled by a memoryless amplifier followed by a linear filter. Equally important, it puts forward the studies concerning the application of different NN training algorithms in order to determine the most prefermant for adaptive predistortions. This comparison examined through computer simulation for 64 carriers and 16-QAM OFDM system, with a Saleh's TWT amplifier, is based on some quality measure (mean square error), the required training time to reach a particular quality level, and computation complexity. The chosen adaptive predistortions (NN structures associated with an adaptive algorithm) have a low complexity, fast convergence, and best performance.
67 citations
TL;DR: Findings show that schemes based on nonuniform quantization of the "soft bits" allow for reducing the backhaul to 1–2 exchanged bits/coded bit, and investigates the effect of quantized log-likelihood ratios (LLRs) with the objective of further reducing theBackhaul traffic.
Abstract: This paper deals with multiuser detection through base station cooperation in an uplink, interference-limited, high frequency reuse scenario. Distributed iterative detection (DID) is an interference mitigation technique in which the base stations at different geographical locations exchange detected data iteratively while performing separate detection and decoding of their received data streams. This paper explores possible DID receive strategies and proposes to exchange between base stations only the processed information for their associated mobile terminals. The resulting backhaul traffic is considerably lower than that of existing cooperative multiuser detection strategies. Single-antenna interference cancellation techniques are employed to generate local estimates of the dominant interferers at each base station, which are then combined with their independent received copies from other base stations, resulting in more effective interference suppression. Since hard information bits or quantized log-likelihood ratios (LLRs) are transferred, we investigate the effect of quantization of the LLR values with the objective of further reducing the backhaul traffic. Our findings show that schemes based on nonuniform quantization of the "soft bits" allow for reducing the backhaul to 1-2 exchanged bits/coded bit.
66 citations
TL;DR: Simulation results show that significant performance gains can be achieved by the proposed bit loading algorithms, especially when subchannel permutation is employed.
Abstract: We investigate the resource allocation problem for an OFDM cooperative network with a single source-destination pair and multiple relays. Assuming knowledge of the instantaneous channel gains for all links in the entire network, we propose several bit and power allocation schemes aiming at minimizing the total transmission power under a target rate constraint. First, an optimal and efficient bit loading algorithm is proposed when the relay node uses the same subchannel to relay the information transmitted by the source node. To further improve the performance gain, subchannel permutation, in which the subchannels are reallocated at relay nodes, is considered. An optimal subchannel permutation algorithm is first proposed and then an efficient suboptimal algorithm is considered to achieve a better complexity-performance tradeoff. A distributed bit loading algorithm is also proposed for ad hoc networks. Simulation results show that significant performance gains can be achieved by the proposed bit loading algorithms, especially when subchannel permutation is employed.
66 citations
TL;DR: The multiuser detection (MUD) in MC DS-CDMA is considered, which motivates lowcomplexity, high flexibility, and robustness so that the MUD schemes are suitable for deployment in dynamic communications environments.
Abstract: In wireless communications, multicarrier direct-sequence code-division multiple access (MC DS-CDMA) constitutes one of the highly flexible multiple access schemes. MC DS-CDMA employs a high number of degrees-of-freedom, which are beneficial to design and reconfiguration for communications in dynamic communications environments, such as in the cognitive radios. In this contribution, we consider the multiuser detection (MUD) in MC DS-CDMA, which motivates low complexity, high flexibility, and robustness so that the MUD schemes are suitable for deployment in dynamic communications environments. Specifically, a range of low-complexity MUDs are derived based on the zero-forcing (ZF), minimum mean-square error (MMSE), and interference cancellation (IC) principles. The bit-error rate (BER) performance of the MC DS-CDMA aided by the proposed MUDs is investigated by simulation approaches. Our study shows that, in addition to the advantages provided by a general ZF, MMSE, or IC-assisted MUD, the proposed MUD schemes can be implemented using modular structures, where most modules are independent of each other. Due to the independent modular structure, in the proposed MUDs one module may be reconfigured without yielding impact on the others. Therefore, the MC DS-CDMA, in conjunction with the proposed MUDs, constitutes one of the promising multiple access schemes for communications in the dynamic communications environments such as in the cognitive radios.
46 citations
TL;DR: This paper studies the performance of space-time coded (STC) multiantenna OFDM systems under I/Q imbalance, covering both the transmitter and the receiver sides of the link, and proposes a practical pilot-based I/ Q imbalance compensation scheme.
Abstract: The combination of orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) techniques has been widely considered as the most promising approach for building future wireless transmission systems. The use of multiple antennas poses then big restrictions on the size and cost of individual radio transmitters and receivers, to keep the overall transceiver implementation feasible. This results in various imperfections in the analog radio front ends. One good example is the so-called I/Q imbalance problem related to the amplitude and phase matching of the transceiver I and Q chains. This paper studies the performance of space-time coded (STC) multiantenna OFDM systems under I/Q imbalance, covering both the transmitter and the receiver sides of the link. The challenging case of frequency-selective I/Q imbalances is assumed, being an essential ingredient in future wideband wireless systems. As a practical example, the Alamouti space-time coded OFDM system with two transmit and M receive antennas is examined in detail and a closed-form solution for the resulting signal-to-interference ratio (SIR) at the detector input due to I/Q imbalance is derived. This offers a valuable analytical tool for assessing the I/Q imbalance effects in any STC-OFDM system, without lengthy data or system simulations. In addition, the impact of I/Q imbalances on the channel estimation in the STC-OFDM context is also analyzed analytically. Furthermore, based on the derived signal models, a practical pilot-based I/Q imbalance compensation scheme is also proposed, being able to jointly mitigate the effects of frequency-selective I/Q imbalances as well as channel estimation errors. The performance of the compensator is analyzed using extensive computer simulations, and it is shown to virtually reach the perfectly matched reference system performance with low pilot overhead.
44 citations
TL;DR: This paper proposes an intelligent solution answering user requirements and ensuring service continuity by focusing on a vertical handover decision strategy based on the context-awareness concept.
Abstract: Future generation wireless networks should provide to mobile users the best connectivity to services anywhere at anytime. The most challenging problem is the seamless intersystem/vertical mobility across heterogeneous wireless networks. In order to answer it, a vertical handover management system is needed. In our paper, we propose an intelligent solution answering user requirements and ensuring service continuity. We focus on a vertical handover decision strategy based on the context-awareness concept. The given strategy chooses the appropriate time and the most suitable access network among those available to perform a handover. It uses advanced decision algorithms (for more efficiency and intelligence) and it is governed by handover policies as decision rules (for more flexibility and optimization). To maintain a seamless service continuity, handover execution is based on mobile IP functionalities. We study our decision system in a case of a 3G/UMTS-WLAN scenario and we discuss all the handover decision issues in our solution.
42 citations
TL;DR: A closed-loop control system for continuous drug infusion is designed to improve the traditional discrete methods and make diabetes therapy automatic in practice and by exploring the accumulative function of drug to insulin, a continuous injection model is proposed.
Abstract: While a typical way for diabetes therapy is discrete insulin infusion based on long-time interval measurement, in this paper, we design a closed-loop control system for continuous drug infusion to improve the traditional discrete methods and make diabetes therapy automatic in practice. By exploring the accumulative function of drug to insulin, a continuous injection model is proposed. Based on this model, proportional-integral-derivative (PID) and fuzzy logic controllers are designed to tackle a control problem of the resulting highly nonlinear plant. Even with serious disturbance of glucose, such as nutrition absorption at meal time, the proposed scheme can perform well in simulation experiments.
TL;DR: The channel selection problem is formulated as a multiarmed bandit problem enabling the optimal selection rules to be derived and the proposed algorithm consistently tracks the best channel compared to other heuristic schemes.
Abstract: This paper addresses the problem of optimal channel selection for spectrum-agile low-powered wireless networks in unlicensed bands. The channel selection problem is formulated as a multiarmed bandit problem enabling us to derive the optimal selection rules. The model assumptions about the interfering traffic that motivates this formulation are also validated through 802.11 traffic measurements as an example of a packet switched network. Finally, the performance of the optimal dynamic channel selection is investigated through simulation. The simulation results show that the proposed algorithm consistently tracks the best channel compared to other heuristic schemes.
TL;DR: Two cyclostationarity-inducing transmission methods that enable the receiver to distinguish among different systems that use a common orthogonal frequency division multiplexing- (OFDM-) based air interface are proposed.
Abstract: This paper proposes two cyclostationarity-inducing transmission methods that enable the receiver to distinguish among different systems that use a common orthogonal frequency division multiplexing-(OFDM-) based air interface. Specifically, the OFDM signal is configured before transmission such that its cyclic autocorrelation function (CAF) has peaks at certain preselected cycle frequencies. The first proposed method inserts a specific preamble where only a selected subset of subcarriers is used for transmission. The second proposed method dedicates a few subcarriers in the OFDM frame to transmit specific signals that are designed so that the whole frame exhibits cyclostationarity at preselected cycle frequencies. The detection probabilities for the proposed cyclostationarity-inducing transmission methods are evaluated based on computer simulation when optimum and suboptimum detectors are used at the receiver.
TL;DR: Primary dualities that have been long studied in the context of cooperative games are studied, including dualities between information inequalities on the one hand and properties of rate, capacity, or other resource allocation regions on the other.
Abstract: Cores of cooperative games are ubiquitous in information theory and arise most frequently in the characterization of fundamental limits in various scenarios involving multiple users. Examples include classical settings in network information theory such as Slepian-Wolf source coding and multiple access channels, classical settings in statistics such as robust hypothesis testing, and new settings at the intersection of networking and statistics such as distributed estimation problems for sensor networks. Cooperative game theory allows one to understand aspects of all these problems from a fresh and unifying perspective that treats users as players in a game, sometimes leading to new insights. At the heart of these analyses are fundamental dualities that have been long studied in the context of cooperative games; for information theoretic purposes, these are dualities between information inequalities on the one hand and properties of rate, capacity, or other resource allocation regions on the other.
TL;DR: In this paper, a training-sequences-aided linear minimum mean square error (LMMSE) channel estimation method is proposed for OFDM-based cooperative diversity systems with multiple AF relays over frequency-selective fading channels.
Abstract: Orthogonal frequency division multiplexing- (OFDM-) based amplify-and-forward (AF) cooperative communication is an effective way for single-antenna systems to exploit the spatial diversity gains in frequency-selective fading channels, but the receiver usually requires the knowledge of the channel state information to recover the transmitted signals In this paper, a training-sequences-aided linear minimum mean square error (LMMSE) channel estimation method is proposed for OFDM-based cooperative diversity systems with multiple AF relays over frequency-selective fading channels The mean square error (MSE) bound on the proposed method is derived and the optimal training scheme with respect to this bound is also given By exploiting the optimal training scheme, an optimal low-rank LMMSE channel estimator is introduced to reduce the computational complexity of the proposed method via singular value decomposition Furthermore, the Chu sequence is employed as the training sequence to implement the optimal training scheme with easy realization at the source terminal and reduced computational complexity at the relay terminals The performance of the proposed low-complexity channel estimation method and the superiority of the derived optimal training scheme are verified through simulation results
TL;DR: Potential emergency communications architecture is proposed and a method for estimating emergency communications systems traffic patterns for a catastrophic event is presented, which could lead to enhanced 911 capabilities using either GPS or reference stations.
Abstract: Natural disasters and terrorist acts have significant potential to disrupt emergency communication systems. These emergency communication networks include first-responder, cellular, landline, and emergency answering services such as 911, 112, or 999. Without these essential emergency communications capabilities, search, rescue, and recovery operations during a catastrophic event will be severely debilitated. High altitude platforms could be fitted with telecommunications equipment and used to support these critical communications missions once the catastrophic event occurs. With the ability to be continuously on station, HAPs provide excellent options for providing emergency coverage over high-risk areas before catastrophic incidents occur. HAPs could also provide enhanced 911 capabilities using either GPS or reference stations. This paper proposes potential emergency communications architecture and presents a method for estimating emergency communications systems traffic patterns for a catastrophic event.
TL;DR: An orthogonally multiplex quadrature amplitude modulation (OQAM-) CDMA combination that permits a perfect reconstruction of the complex symbols transmitted over a distortion-free channel.
Abstract: We propose an alternative to the well-known multicarrier code-division multiple access (MC-CDMA) technique for downlink transmission by replacing the conventional cyclic-prefix orthogonal frequency division multiplexing (OFDM) modulation by an advanced filterbank-based multicarrier system (OFDM/OQAM). Indeed, on one hand, MC-CDMA has already proved its ability to fight against frequency-selective channels thanks to the use of the OFDM modulation and its high flexibility in multiple access thanks to the CDMA component. On the other hand, OFDM/OQAM modulation confers a theoretically optimal spectral efficiency as it operates without guard interval. However, its orthogonality is limited to the real field. In this paper, we propose an orthogonally multiplex quadrature amplitude modulation (OQAM-) CDMA combination that permits a perfect reconstruction of the complex symbols transmitted over a distortion-free channel. The validity and efficiency of our theoretical scheme are illustrated by means of a comparison, using realistic channel models, with conventional MC-CDMA and also with an OQAM-CDMA combination conveying real symbols.
TL;DR: A novel platform for advanced transmission of medical image and video, introducing context awareness in telemedicine systems is presented, based on scalable wavelet compression with region-of-interest support for images and adaptive H.264 coding for video.
Abstract: The aim of this paper is to present a novel platform for advanced transmission of medical image and video, introducing context awareness in telemedicine systems. Proper scalable image and video compression schemes are applied to the content according to environmental properties (i.e., the underlying network status, content type, and the patient status). The transmission of medical images and video for telemedicine purposes is optimized since better content delivery is achieved even in the case of low-bandwidth networks. An evaluation platform has been developed based on scalable wavelet compression with region-of-interest support for images and adaptive H.264 coding for video. Corresponding results of content transmission over wireless networks (i.e., IEEE 802.11e, WiMAX, and UMTS) have proved the effectiveness and efficiency of the platform.
TL;DR: This work examines the achievable rate and capacity regions of single user cognitive channels and considers a cognitive network with a single primary user and multiple cognitive users, showing that with single-hop transmission, the sum capacity of the cognitive users scales linearly with the number of users.
Abstract: Cognitive radios have the potential to vastly improve communication over wireless channels. We outline recent information theoretic results on the limits of primary and cognitive user communication in single and multiple cognitive user scenarios. We first examine the achievable rate and capacity regions of single user cognitive channels. Results indicate that at medium SNR (0-20 dB), the use of cognition improves rates significantly compared to the currently suggested spectral gap-filling methods of secondary spectrum access. We then study another information theoretic measure, the multiplexing gain. This measure captures the number of point-to-point Gaussian channels contained in a cognitive channel as the SNR tends to infinity. Next, we consider a cognitive network with a single primary user and multiple cognitive users. We show that with single-hop transmission, the sum capacity of the cognitive users scales linearly with the number of users. We further introduce and analyze the primary exclusive radius, inside of which primary receivers are guaranteed a desired outage performance. These results provide guidelines when designing a network with secondary spectrum users.
TL;DR: It is pointed out that due to its moderate complexity but very good performance, directed or iterated PTS using combined weighting and temporal shifting is a very attractive candidate for PAR reduction in future multiantenna OFDM schemes.
Abstract: The major drawback of orthogonal frequency-division multiplexing (OFDM) is its high peak-to-average power ratio (PAR), which gets even more substantial if a transmitter with multiple antennas is considered. To overcome this problem, in this paper, the partial transmit sequences (PTS) method--well known for PAR reduction in single antenna systems--is studied for multiantenna OFDM. A directed approach, recently introduced for the competing selected mapping (SLM) method, proves to be very powerful and able to utilize the potential of multiantenna systems. To apply directed PTS, various variants for providing a sufficiently large number of alternative signal superpositions (the candidate transmit signals) are discussed. Moreover, affording the same complexity, it is shown that directed PTS offers better performance than SLM. Via numerical simulations, it is pointed out that due to its moderate complexity but very good performance, directed or iterated PTS using combined weighting and temporal shifting is a very attractive candidate for PAR reduction in future multiantenna OFDM schemes.
TL;DR: Investigation of clear channel assessment (CCA) and its impact on the coexistence of WLAN and WPAN in the 2.4 GHz industrial, scientific, and medical band finds inequality asymmetric CCA leads to WPAN traffic in a position secondary to WLAN traffic.
Abstract: Complementary WLAN and WPAN technologies as well as other wireless technologies will play a fundamental role in the medical environments to support ubiquitous healthcare delivery. This paper investigates clear channel assessment (CCA) and its impact on the coexistence of WLAN (IEEE 802.11 high rate direct sequence spread spectrum (HR/DSSS) PHY) andWPAN (IEEE 802.15.4b) in the 2.4 GHz industrial, scientific, and medical (ISM) band.We derived closed-form expressions of both energy-based CCA and feature-based CCA. We qualified unequal sensing abilities between them and termed this inequality asymmetric CCA, which is different from the traditional "hidden node" or "exposed node" issues in the homogeneous network. The energy-based CCA was considered in the considered integratedmedical environment because the 2.4 GHz ISM band is too crowded to apply feature-based CCA. The WPAN is oversensitive to the 802.11 HR/DSSS signals and the WLAN is insensitive to the 802.15.4b signals. Choosing an optimal CCA threshold requires some prior knowledge of the underlying signals. In the integrated medical environment we considered here, energy-based CCA can effectively avoid possible packet collisions when they are close within the "heterogeneous exclusive CCA range" (HECR). However, when they are separated beyond the HECR, WPAN can still sense the 802.11 HR/DSSS signals, but WLAN loses its sense to the 802.15.4b signals. The asymmetric CCA leads to WPAN traffic in a position secondary to WLAN traffic.
TL;DR: A multievent congestion control protocol (MCCP) for wireless sensor networks that efficiently mitigates congestion and provides output according to selected event reporting mode, and decreases packet drops and provides high packet delivery ratio for multiple event reporting modes.
Abstract: Wireless sensor networks are application-dependent networks. An application may require general event region information, pernode event region information, or prioritized event information in case of multiple events. All event flows are subject to congestion in wireless sensor networks. This is due to the sudden impulse of information flow from a number of event nodes to a single destination. Congestion degrades system throughput and results in energy loss of nodes. In this paper, we present a multievent congestion control protocol (MCCP) for wireless sensor networks. MCCP supports multiple event reporting modes, that is, general event reporting, per-node fair event reporting, and prioritized multiple event reporting. MCCP efficiently mitigates congestion and provides output according to selected event reporting mode. MCCP uses hop-by-hop packet delivery time and buffer size as the basic metrics for congestion detection. Moreover, we introduce a schedule-based scheme at the transport layer for rate assignment and ordered delivery of event packets to underlying routing layer. This helps to avoid packet collisions and increases the packet delivery ratio even in high densities. Detailed simulation analysis confirms that MCCP decreases packet drops and provides high packet delivery ratio (above 90%) for multiple event reporting modes.
TL;DR: This paper focuses on a handoff triggering criterion which uses both the RSS and distance information, and a network selection method which uses context information such as the dropping probability, blocking probability, GoS (grade of service), and number of handoff attempts.
Abstract: This paper proposes a novel vertical handoff algorithm between WLAN and CDMA networks to enable the integration of these networks. The proposed vertical handoff algorithm assumes a handoff decision process (handoff triggering and network selection). The handoff trigger is decided based on the received signal strength (RSS). To reduce the likelihood of unnecessary false handoffs, the distance criterion is also considered. As a network selection mechanism, based on the wireless channel assignment algorithm, this paper proposes a context-based network selection algorithm and the corresponding communication algorithms between WLAN and CDMA networks. This paper focuses on a handoff triggering criterion which uses both the RSS and distance information, and a network selection method which uses context information such as the dropping probability, blocking probability, GoS (grade of service), and number of handoff attempts. As a decision making criterion, the velocity threshold is determined to optimize the system performance. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations using four handoff strategies. The four handoff strategies are evaluated and compared with each other in terms of GOS. Finally, the proposed scheme is validated by computer simulations.
TL;DR: A single antenna interference cancellation (SAIC) algorithm is introduced for amplitude-shift keying (ASK) modulation schemes in combination with bit-interleaved coded OFDM and it is shown that high gains in comparison to a conventional OFDM transmission with quadrature amplitude modulation (QAM) can be achieved.
Abstract: Radio networks for future mobile communications systems, for example, 3GPP Long-Term Evolution (LTE), are likely to use an orthogonal frequency division multiplexing- (OFDM-) based air interface in the downlink with a frequency reuse factor of one to avoid frequency planning. Therefore, system capacity is limited by interference, which is particularly crucial for mobile terminals with a single receive antenna. Nevertheless, next generation mobile communications systems aim at increasing downlink throughput. In this paper, a single antenna interference cancellation (SAIC) algorithm is introduced for amplitude-shift keying (ASK) modulation schemes in combination with bit-interleaved coded OFDM. By using such a transmission strategy, high gains in comparison to a conventional OFDM transmission with quadrature amplitude modulation (QAM) can be achieved. The superior performance of the novel scheme is confirmed by an analytical bit-error probability (BEP) analysis of the SAIC receiver for a single interferer, Rayleigh fading, and uncoded transmission. For the practically more relevant multiple interferer case we present an adaptive least-mean-square (LMS) and an adaptive recursive least-squares (RLS) SAIC algorithm. We show that in particular the RLS approach enables a good tradeoff between performance and complexity and is robust even to multiple interferers.
TL;DR: Analysis in the low signal-to-noise ratio regime and numerical results validate the advantages of conferencing as a complementary technology to multicell processing.
Abstract: This paper considers an enhancement to multicell processing for the uplink of a cellular system, whereby the mobile stations are allowed to exchange messages on orthogonal channels of fixed capacity (conferencing). Both conferencing among mobile stations in different cells and in the same cell (inter- and intracell conferencing, resp.) are studied. For both cases, it is shown that a rate-splitting transmission strategy, where part of the message is exchanged on the conferencing channels and then transmitted cooperatively to the base stations, is capacity achieving for sufficiently large conferencing capacity. In case of intercell conferencing, this strategy performs convolutional pre-equalization of the signal encoding the common messages in the spatial domain, where the number of taps of the finite-impulse response equalizer depends on the number of conferencing rounds. Analysis in the low signal-to-noise ratio regime and numerical results validate the advantages of conferencing as a complementary technology to multicell processing.
TL;DR: A detection algorithm based on a cost function that jointly tests the correlation induced by the cyclic prefix and the fact that this correlation is time-periodic is proposed and estimated that the proposed algorithm detects DVB-T signals with an SNR of dB.
Abstract: We propose in this paper a detection algorithm based on a cost function that jointly tests the correlation induced by the cyclic prefix and the fact that this correlation is time-periodic. In the first part of the paper, the cost function is introduced and some analytical results are given. In particular, the noise and multipath channel impacts on its values are theoretically analysed. In a second part of the paper, some asymptotic results are derived. A first exploitation of these results is used to build a detection test based on the false alarm probability. These results are also used to evaluate the impact of the number of cycle frequencies taken into account in the cost function on the detection performances. Thanks to numerical estimations, we have been able to estimate that the proposed algorithm detects DVB-T signals with an SNR of -12 dB. As a comparison, and in the same context, the detection algorithm proposed by the 802.22 WG in 2006 is able to detect these signals with an SNR of -8 dB.
TL;DR: In this article, the complexity analysis of Reed-Solomon (RS) codes over characteristic-2 fields has been studied and compared to the complexity of syndrome-based decoding algorithms.
Abstract: There has been renewed interest in decoding Reed-Solomon (RS) codes without using syndromes recently. In this paper, we investigate the complexity of syndromeless decoding, and compare it to that of syndrome-based decoding. Aiming to provide guidelines to practical applications, our complexity analysis focuses on RS codes over characteristic-2 fields, for which some multiplicative FFT techniques are not applicable. Due to moderate block lengths of RS codes in practice, our analysis is complete, without big O notation. In addition to fast implementation using additive FFT techniques, we also consider direct implementation, which is still relevant for RS codes with moderate lengths. For high-rate RS codes, when compared to syndrome-based decoding algorithms, not only syndromeless decoding algorithms require more field operations regardless of implementation, but also decoder architectures based on their direct implementations have higher hardware costs and lower throughput. We also derive tighter bounds on the complexities of fast polynomial multiplications based on Cantor's approach and the fast extended Euclidean algorithm.
TL;DR: A frame dropping mechanism allows the system to avoid unnecessary channel use, when the analytical estimations show that the successful decoding of a given frame is not possible because of very high motion or bad channel conditions.
Abstract: We present a novel rate allocation technique for distributed multiuser video coding systems without the need for a permanent feedback channel. Based on analytical calculations, the system unequally distributes the available bandwidth among the different users, taking into account the actual amount of movement in the transmitted video as well as the transmission conditions of each user. On one hand, the quantization parameters are dynamically tuned in order to optimize the decoding quality. On the other hand, a frame dropping mechanism allows the system to avoid unnecessary channel use, when the analytical estimations show that the successful decoding of a given frame is not possible because of very high motion or bad channel conditions. A significant gain in the system performance is noticed compared with the case of equal allocation of channel resources and constant quantization parameters.
TL;DR: This work proposes a dynamic key management protocol, which can improve the security of the key juxtaposed to existing methods and lower the probability of thekey to being guessed correctly.
Abstract: Recently, wireless sensor networks have been used extensively in different domains. For example, if the wireless sensor node of a wireless sensor network is distributed in an insecure area, a secret key must be used to protect the transmission between the sensor nodes. Most of the existing methods consist of preselecting keys from a key pool and forming a key chain. Then, the sensor nodes make use of the key chain to encrypt the data. However, while the secret key is being transmitted, it can easily be exposed during transmission. We propose a dynamic key management protocol, which can improve the security of the key juxtaposed to existing methods. Additionally, the dynamic update of the key can lower the probability of the key to being guessed correctly. In addition, with the new protocol, attacks on the wireless sensor network can be avoided.