Cooperative communication is a promising strategy to enhance the performance of a communication network as it helps to improve the coverage area and the outage performance. However, such enhancement comes at the expense of increased resource utilization, which is undesirable; more so in the case of opportunistic wireless systems such as cognitive radio networks. In order to balance the performance gains from cooperative communication against the possible over-utilization of resources, we propose and analyze an adaptive-cooperation technique for underlay cognitive radio networks, termed as hybrid-cooperation. Under the proposed cooperation scheme, secondary users in a cognitive radio network cooperate adaptively to enhance the spectral efficiency and the error performance of the network. The bit error rate, the spectral efficiency and the outage performance of the network under the proposed hybrid cooperation scheme with amplify-and-forward relaying are analyzed in this paper, and compared against conventional cooperation technique. Findings of the analytical performance analyses are further validated numerically through selected computer-based Monte-Carlo simulations. The proposed scheme is found to achieve significantly better performance in terms of the spectral efficiency and the bit error rate, compared to the conventional amplify-and-forward cooperation scheme.

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

In practical wireless networks, the available transmission power and bandwidth are limited resources. Therefore, joint bandwidth and power allocation for wireless multi-user networks is essential in order to improve the network performance. Most of the research has focused on continuous rate, power, and bandwidth allocations in the presence of perfect channel knowledge. However, this is not the case with practical systems. In this paper, we therefore consider the issue of discrete power and bandwidth allocation for discrete-rate multi-user link adaptation with imperfect channel state information. To be more specific, we discuss how the system can be designed in such a scenario for i) sum rate maximization and ii) average power minimization in a multi-user setting. The results show that with only a few codes, we can approach the performance of systems that employ continuous (infinite) rates. We have also found that imperfect channel information at the base station affects the performance such that the sum rate is decreased and the average power consumption is increased.

In our earlier work, we described an optimization problem and corresponding scheduling algorithm aimed at obtaining maximum throughput guarantees in wireless networks. To further improve the short-term performance, we also proposed two adaptive versions of the optimal algorithm. Results from the simulations showed that the adaptive algorithms perform significantly better than other well-known scheduling algorithms in networks based on Mobile WiMAX, HSDPA, LTE and WINNER I. However, there were several idealistic assumptions in that analysis, the most important of which is that each user estimates its carrier-to-noise ratio (CNR) perfectly, and there is no feedback delay. In practice however, the channel estimation is not perfect, and there is always some delay in the feedback channel. In this paper, we assume that a maximum a posteriori (MAP) predictor is employed for the CNR, so that the system takes the feedback delay and the channel noise into account. We then investigate the effect of imperfect channel prediction and delay on the throughput guarantees promised to all the users in the wireless network. A procedure to reduce the probability of outage in case of imperfect channel prediction is also proposed.

In this paper, we investigate the spectral efficiency of vector precoding with minimum mean square error (MMSE) linear preprocessing. We restrict the discussion to the spectral efficiency of MMSE vector precoding with quadrature phase-shift keying (QPSK) signaling. Spectral efficiency is investigated by numerical simulations, and plotted as a function of the energy per bit divided by the noise spectral density Eb/N0. The optimum system load α, given as the ratio of the number of transmit and receive antennas, that maximizes spectral efficiency is obtained. Previously obtained spectral efficiency results for: Dirty paper coding (DPC), linear zero forcing (ZF), ZF vector precoding, and linear MMSE precoding are provided for comparison. We quantify the performance enhancement that MMSE vector precoding obtains in comparison to vector precoding with ZF linear preprocessing, in the low to medium Eb/N0region. We also find that MMSE vector precoding does not significantly outperform its linear counterpart.

Offering throughput guarantees for cellular wireless networks, carrying real-time traffic, is of interest to both the network operators and the customers. Furthermore, to be able to quantify the soft throughput guarantees for a certain scheduling algorithm without conducting experimental investigations, is valuable for network providers. In this paper, we develop an expression for the approximate throughput guarantee violation probability (TGVP) for users in time-slotted networks with the given cumulants of the distribution of the bit-rate, and a given distribution for the number of time-slots allocated within a time-window. Through simulations, it is shown that this TGVP approximation is tight for a realistic wireless network with moving users and correlated channels.

In this paper, the performance of the ALOHA and CSMA MAC protocols are analyzed in spatially distributed wireless networks. The main system objective is correct reception of packets, and thus the analysis is performed in terms of outage probability. In our network model, packets belonging to specific transmitters arrive randomly in space and time according to a 3-D Poisson point process, and are then transmitted to their intended destinations using a fully-distributed MAC protocol. A packet transmission is considered successful if the received SINR is above a predefined threshold for the duration of the packet. Accurate bounds on the outage probabilities are derived as a function of the transmitter density, the number of backoffs and retransmissions, and in the case of CSMA, also the sensing threshold. The analytical expressions are validated with simulation results. For continuous-time transmissions, CSMA with receiver sensing (which involves adding a feedback channel to the conventional CSMA protocol) is shown to yield the best performance. Moreover, the sensing threshold of CSMA is optimized. It is shown that introducing sensing for lower densities (i.e., in sparse networks) is not beneficial, while for higher densities (i.e., in dense networks), using an optimized sensing threshold provides significant gain.

Cognitive radio offers an attractive means of utilizing spectral resources opportunistically, yet relies on an agreement that the secondary users do not interfere with the primary users. This system-wide constraint makes distributed resource allocation difficult. In this paper, sum rates for a multiuser cognitive radio system under received power constraints are derived and optimal and suboptimal power assignments are found for orthogonal resource sharing and simultaneous transmission scenarios. By allocating a portion of the primary user constraints to each basestation, a novel rate-maximizing distributed technique by which each multi-antenna basestation controls the parameters of its own secondary users is proposed and evaluated. Though suboptimal, the computational burden of the proposed algorithm is minimal compared to the NP-hard optimal solution.

This paper considers the impact of backoffs and retransmissions on the performance of the ALOHA and CSMA protocols in wireless mobile ad hoc networks. In our network model, packets belonging to specific transmitters arrive randomly in space and time according to a 3-D PPP, and are then transmitted to their intended destinations using a fully-distributed MAC protocol. A packet transmission is considered successful if it is initiated and the received SINR is above a predefined threshold for the duration of the packet. Approximate expressions are derived for the outage probability of ALOHA (slotted and unslotted) and CSMA (with transmitter sensing and with receiver sensing), as a function of the transmission density and the number of backoff and retransmission attempts. Simulations verify our analytical expressions, and it is shown that the outage probability is a decreasing function of the maximum allowable number of backoffs and retransmissions. By allowing for high number of backoffs, CSMA with receiver sensing can even outperform slotted ALOHA. For high number of retransmissions, however, ALOHA may outperform CSMA. Finally, the average transmission delay of packets is also evaluated through simulations.

In this paper we propose a modification of the Hopfield neural networks for vector precoding, based on Lenstra, Lenstra, and Lovasz lattice basis reduction. This precoding algorithm controls the energy penalty for system loads α = K/N close to 1, with N and K denoting the number of transmit and receive antennas, respectively. Simulation results for the average transmit energy as a function of α show that our algorithm improves performance within the range 0.9 ≤ α ≤ 1, between 0.4 dB and 2.6 dB in comparison to standard HNN precoding. The proposed algorithm performs close to the sphere encoder (SE) while requiring much lower complexity, and thus, can be applied as an efficient suboptimal precoding method.

This paper considers the tradeoff between bursty and continuous transmissions in wireless ad hoc networks. In our network model, packets belonging to specific transmitters arrive randomly in space and time according to a 3-D Poisson point process, and are then transmitted to their intended destinations using a fully-distributed MAC protocol (ALOHA or CSMA). Stochastic SINR measurements are used to determine whether or not a packet has been received successfully. The objective of this work is to maximize the probability of successful transmissions by optimizing the transmission rate and duration of packets. Approximate analytical expressions are derived for the outage probability of ALOHA and CSMA, and their performances are evaluated. The optimal spectral efficiency and packet duration of ALOHA is found analytically, and that of CSMA is obtained through simulations. CSMA is shown to yield the best performance both in terms of minimum achievable outage probability and the corresponding spectral efficiency.

In this work, we first study and then propose an optimal version on the medium access control mechanism known as carrier sense multiple access with collision avoidance (CSMA/CA). This protocol is adopted by many wireless communication standards, such as the IEEE 802.11 series and IEEE 802.15.4 (ZigB

In this paper, we develop two different approaches for the centralized joint power and bandwidth allocation problem. We aim to maximize the uplink sum rate with multiple base stations. First, we exploit the convex approximation with series of Geometric Programming (GP) formulations. Then, we propose a novel, iterative method that is enhanced with scheduling to improve both convergence speed and sum rate. The problem is handled in an interference-limited multiband system using power and interference constraints. Our numerical experiments illustrate that the new iterative method's sum rate performance is comparable to the GP, within small number of iterations and lower complexity.

In this paper we consider pure line-of-sight multiple-input multiple-output (MIMO) channels employing uniform linear antenna arrays. We investigate the influence of exact spherical wave propagation modeling versus approximate plane wave propagation modeling on the properties of the MIMO channel matrix. When the transmission distance increases, the properties of the singular values of the MIMO channel matrix given by the spherical wave model approach the properties given by the simpler plane wave model. We investigate this transition between the two channel models, which results in a new tool giving us analytical expressions describing when spherical wave modeling is necessary and when plane wave modeling gives sufficient modeling accuracy. The parameters of interest are the transmission distance, the frequency, the array orientation, and the array size. The tool introduced is general, in the sense that it supports different performance measures when deciding on the transition between the two models. As an example, we investigate underestimation of the mutual information in this paper. The results show that the spherical wave model should be applied e.g. in some practical WLAN scenarios where plane wave modeling is commonly applied today.

Network-wide optimization of transmit power with the goal of maximizing the total throughput, promises significant system capacity gains in interference-limited data networks. Finding distributed solutions to this global optimization problem however, remains a challenging task. In this work, we first focus on the maximization of the weighted sum-rate capacity, as this allows the incorporation of QoS criteria in the objective function. For the case of two links, we are able to analytically characterize the optimal solution to the weighted sum-rate maximization problem. However, computing the optimal solution requires centralized knowledge of network information. We thus formulate a framework for distributed power optimization valid for N mutually interfering links, based on the concept of channel state partitioning. By assuming instantaneous knowledge of local information and statistical knowledge of non-local information, we derive a distributed power allocation algorithm, which we first analyze for the case of N = 2. Although a gain is observed over equal power allocation, the distributed algorithm shows a performance gap as compared to a centralized solution, as expected. We show however, that minimal information message passing (in this case one bit) between interfering links can help reduce this gap substantially. Finally, we also propose a method to incorporate user scheduling into the distributed power allocation algorithm.

In this paper, we discuss a certain route configuration problem via optimization theory. The problem is potentially relevant for designers of both wireless sensor and wireless ad hoc networks with multihop and link adaptation capability. We consider the optimal bit error rate (BER) and transmission rate allocations subject to overall BER and delay constraints for a designated route. The pivot of the problem lies in the delay constraint, which divides the problem into two cases - the loose delay and the tight delay case. In the former, analytical solutions are obtained by applying the Karush-Kuhn-Tucker (KKT) theorem. Specifically, we discover in this case that for a given target BER, the optimum solutions are only related to the hop lengths in the route. When the delay constraint is tight, there exists a mapping which can be used to reduce the dimension of the problem by a factor of two; however, a numerical optimization algorithm has to be used to find the optimum. The problem can however be shown to be a convex optimization problem, which ensures that any local minimum will be global. Simulation results show that by optimally configuring a chosen route, substantial energy savings could be obtained, especially under tight delay constraints.

We consider the downlink of a cognitive radio network consisting of multiple secondary transmitter and receiver communicating simultaneously in the presence of one primary user. The key idea within this paper is to combine multi-user diversity gains with spectral sharing techniques through inter-system coordination, in order to maximize the secondary user sum rate while maintaining a guaranteed quality of service (QoS) to a primary user. We first present a distributed power allocation algorithm that maximizes the capacity of the cognitive ratio network. The algorithm is simple to implement, since a secondary user can decide to either transmit data or stay silent over the channel coherence time depending on a specified threshold without affecting the primary users QoS. Then, we analyze performance of such an algorithm in terms of number of cognitive users able to transmit while minimizing interference to guarantee QoS for the primary user. Simulation results carried out based on a realistic network setting showed promising results.

This paper considers the performance of the MAC protocols ALOHA and CSMA in wireless ad hoc networks, where the total system bandwidth may be divided into smaller subbands. In the network model used, the arrival of users/packets follows a Poisson point process, communication between nodes is continuous in time, selection of a subband to transmit across is made randomly at each transmitter, and the outage assessments made in the network are based on SINR measurements. Accurate bounds on the probability of outage for the MAC protocols are derived, and evaluated with respect to the number of subbands. It is observed that there exists an optimal number of subbands for each protocol, for which the probability of outage is minimized. For ALOHA, we obtain an analytical expression for this optimal value, while in CSMA, the optimal value is observed through simulations. Furthermore, we improve the performance of CSMA by introducing channel sensing across all subbands, in order to decrease the probability that a packet is in outage upon arrival. The obtained results are used to compare the performance of the two MAC protocols. Finally, we also evaluate the performance of our network in terms of sum capacity.

In this paper, we propose MICRO (MInimum cost routing with optimized data fusion), an energy-efficient routing protocol for event-driven dense wireless sensor networks. The proposed routing protocol is an improvement over PEGASIS, which exploits a new cost function for energy balancing among sensor nodes and uses an iterative scheme with optimized data fusions to compute the minimum-cost route for each event-detecting sensor node. Compared to the previously suggested PEGASIS routing protocol, the MICRO protocol substantially improves the energy-efficiency of each route by optimizing the trade-off between minimizing the total energy consumption of each route and balancing the energy state of each sensor node. It is demonstrated that the MICRO protocol is able to outperform the LEACH and the PEGASIS protocols with respect to network lifetime by 100 - 300% and 10 - 100%, respectively.

In this paper we derive exact expressions for the mutual information (MI) probability density function and the MI cumulative distribution function of dual-branch multipleinput multiple-output (MIMO) systems (either two transmit (Tx) or two receive (Rx) antennas) communicating over a Ricean channel with no constraint on the rank of the line-of-sight (LOS) channel matrix. This is done both for the case where the channel is only known at the Rx, and for the case where the channel is known both at the Tx and the Rx. As an example, to evaluate the expressions, we employ uniform linear arrays and give expressions for the eigenvalues of the LOS channel matrix for the dual-branch case.

In this letter, a performance analysis of a dualbranch switched diversity system operating on statistically independent and identically distributed Nakagami-m flat-fading channels is presented. An adaptive coded modulation (ACM) scheme is employed to increase the spectral efficiency of the system. The ACM scheme consists of a set of multidimensional trellis codes originally designed for additive white Gaussian noise channels, where the codes are based on quadrature amplitude modulation (QAM) signal constellations of varying size. The performance is evaluated by assuming perfect channel knowledge at both transmitter and receiver and instantaneous feedback of channel state information, conveyed from the receiver to the transmitter on an error-free feedback channel. The optimal switching threshold of the switched diversity combiner, maximizing the average spectral efficiency, is identified for spatially uncorrelated antenna branches.

The memoryless noncoherent single-input-single-output (SISO) Rayleigh-fading channel is considered. Closed-form expressions are derived for the mutual information between the output and the input of this channel when the input magnitude distribution is discrete and is restricted to having two mass points. It is subsequently shown how these expressions can be used to obtain closed-form expressions for the capacity of this channel for signal to noise ratio (SNR) values of up to approximately 0 dB, and a tight capacity lower bound for SNR values between 0 dB and 10 dB. The expressions for the channel capacity and its lower bound are given as functions of a parameter which can be obtained via numerical root-finding algorithms.

We consider allocating the transmit powers for a wireless multi-link (N-link) system, in order to maximize the total system throughput under interference and noise impairments, and short term power constraints. Employing dynamic spectral reuse, we allow for centralized control. In the two-link case, the optimal power allocation then has a remarkably simple nature termed binary power control: depending on the noise and channel gains, assign full power to one link and minimum to the other, or full power on both. Binary power control (BPC) has the advantage of leading towards simpler or even distributed power control algorithms. For N>2 we propose a strategy based on checking the corners of the domain resulting from the power constraints to perform BPC. We identify scenarios in which binary power allocation can be proven optimal also for arbitrary N. Furthermore, in the general setting for N>2, simulations demonstrate that a throughput performance with negligible loss, compared to the best non-binary scheme found by geometric programming, can be obtained by BPC. Finally, to reduce the complexity of optimal binary power allocation for large networks, we provide simple algorithms achieving 99% of the capacity promised by exhaustive binary search.

We consider the problem of finding low-complexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario under the framework of diversity combining. Capitalizing on recent results for joint adaptive modulation and diversity combining schemes (AMDC), we design and analyze two AMDC schemes that utilize power control to reduce the radiated power, and thus the potential interference to other systems/users. Based on knowledge of the channel fading, the proposed schemes adaptively select the signal constellation, diversity combiner structure, and transmit power level. We show that the novel schemes also provide significant average transmit power gains compared to existing joint adaptive QAM and diversity schemes. In particular, over a large signal to noise ratio range, the transmitted power is reduced by 30-50%, yielding a substantial decrease in interference to co-existing systems/users, while maintaining high average spectral efficiency, low combining complexity, and compliance with bit error rate constraints.

Joint optimization of transmit power and scheduling in wireless data networks promises significant system-wide capacity gains. However, this problem is known to be NP-hard and thus difficult to tackle in practice. We analyze this problem for the downlink of a multicell full reuse network with the goal of maximizing the overall network capacity. We propose a distributed power allocation and scheduling algorithm which provides significant capacity gain for any finite number of users. This distributed cell coordination scheme, in effect, achieves a form of dynamic spectral reuse, whereby the amount of reuse varies as a function of the underlying channel conditions and only limited inter-cell signaling is required.

The power adaptation strategy which maximises the average information rate that can be reliably transmitted over average and peak power constrained block-fading single-user discrete-time channels, in which perfect transmitter and receiver channel state information (CSI) are available and in which any transmitted codeword spans a single fading block, is characterised by means of a theorem and subsequently computed numerically in different scenarios. The results reveal striking differences between the well known water-pouring power adaptation strategy which is optimal from a capacity point of view in the case of stationary and ergodic fading channels where the input is subject to an average power constraint only, and the rate-optimal power adaptation strategy of the average and peak power constrained block-fading channels studied in this document.

A sensible design of wireless networks involves striking a good balance between an aggressive reuse of the spectral resource throughout the network and managing the resulting co-channel interference. Traditionally, this problem has been tackled using a ldquodivide and conquerrdquo approach. The latter consists in deploying the network with a static or semidynamic pattern of resource reutilization. The chosen reuse factor, while sacrificing a substantial amount of efficiency, brings the interference to a tolerable level. The resource can then be managed in each cell so as to optimize the per cell capacity using an advanced air interface design. In this paper, we focus our attention on the overall network capacity as a measure of system performance. We consider the problem of resource allocation and adaptive transmission in multicell scenarios. As a key instance, the problem of joint scheduling and power control simultaneously in multiple transmit-receive links, which employ capacity-achieving adaptive codes, is studied. In principle, the solution of such an optimization hinges on tough issues such as the computational complexity and the requirement for heavy receiver-to-transmitter feedback and, for cellular networks, cell-to-cell channel state information (CSI) signaling. We give asymptotic properties pertaining to rate-maximizing power control and scheduling in multicell networks. We then present some promising leads for substantial complexity and signaling reduction via the use of newly developed distributed and game theoretic techniques.

This paper describes a technique for realizing a high-rank channel matrix in a line-of-sight (LOS) multiple-input multiple-output (MIMO) transmission scenario. This is beneficial for systems which are unable to make use of the originally derived MIMO gain given by independent and identically distributed (i.i.d.) flat Rayleigh fading subchannels. The technique is based on optimization of antenna placement in uniform linear arrays with respect to mutual information (MI). By introducing a new and more general 3-D geometrical model than that applied in earlier work, additional insight into the optimal design parameters is gained. We also perform a novel analysis of the sensitivity of the optimal design parameters, and derive analytical expressions for the eigenvalues of the pure LOS channel matrix which are valid also when allowing for non-optimal design. Furthermore, we investigate the approximations introduced in the derivations, in order to reveal when the results are applicable. The LOS matrix is employed in a Ricean fading channel model, and performance is evaluated with respect to the average MI and the MI cumulative distribution function. Our results show that even with some deviation from the optimal design, the LOS MEMO case outperforms the i.i.d. Rayleigh case in terms of MI.

In this paper, performance of a rate-adaptive multiple-input multiple-output diversity system with imperfect channel state information is analyzed and optimized. Space-time block coding is utilized to exploit spatial diversity and to thereby combat some of the fading in wireless channel communications. The remaining fading is tacked by means of adaptive coded modulation. The pilot symbol period and the power allocated to pilot and data symbols are optimized in such a way that the average spectral efficiency is maximized. At the same time, the instantaneous (with respect to predicted channel-signal-to-noise ratio) bit error rate is maintained below a desired level. The average time duration that the channel stays within a certain interval, the average fade region duration, is also derived. A numerical example is given for uncorrelated flat Rayleigh fading subchannels with Jakes spectrum

In this paper we propose a channel state feedback algorithm that uses multiple feedback thresholds to reduce the number of users transmitting feedback to a minimum. The users are polled with lower and lower threshold values and only the users that are above a threshold value transmit feedback to the base station. We show how this feedback algorithm can be used for any scheduling algorithm and show how closed-form expressions for the optimal threshold values can be obtained for two well-known scheduling algorithms. Finally, we propose a two-step optimization procedure for optimizing the feedback algorithm for real-life cellular standards.

In this letter we develop an expression for the approximate throughput guarantee violation probability (TGVP) for users in time-slotted networks for any scheduling algorithm with a given mean and variance of the bit-rate in a time-slot, and a given distribution for the number of time-slots allocated within a time-window. Based on this general result, we evaluate closed-form expressions for the TGVPs for four well-known scheduling algorithms. Through simulations we also show that our TGVP approximation is tight for a realistic network with moving users with correlated channels and realistic throughput guarantees.

In this paper we consider pure line-of-sight multiple-input multiple-output channels employing uniform linear antenna arrays. We investigate the influence of exact spherical wave propagation modeling versus approximate plane wave propagation modeling on the properties of the channel matrix. Our earlier work on 2 times 2 systems is extended to include arbitrary MIMO dimensions. As before, when transmission distance increases, the properties of the spherical wave model converge to the properties given by the simpler plane wave model. The investigation results in a new tool which gives us analytical expressions describing when spherical wave modeling is necessary and when plane wave modeling is sufficient. The parameters of interest are the transmission distance, the frequency, and the array size, and the results show that the spherical wave model should be applied e.g. in some practical WLAN scenarios where plane wave modeling is commonly applied today.

In this paper we analyze achievable throughput guarantees in wireless time-division multiplexing (TDM) networks. Approximations of the throughput guarantee violation probability (TGVP) for users communicating in time-slotted systems are obtained for any scheduling algorithm with a given mean and variance of the number of bits transmitted in a time- slot and a distribution for the number of time-slots allocated to a user within a time-window. We investigate the corresponding TGVPs for three scheduling algorithms, namely (i) Round Robin Scheduling, (ii) Maximum Carrier-to-Noise Ratio Scheduling, and (iii) Opportunistic Round Robin Scheduling, when the users' channels are independently and identically distributed.

In wireless communications, bandwidth is a scarce resource. By employing link adaptation we achieve bandwidth-efficient wireless transmission schemes. Using a fixed number of codes we propose a variable-power transmission scheme for slowly flat-fading channels. Assuming that capacity-achieving codes for AWGN channels are available, we develop new combined discrete-rate discrete-power adaptation algorithms with limited feedback for wireless systems. The adaptation schemes are optimized in order to maximize the average spectral efficiency (ASE) for any finite number of available rates. We show that the new transmission schemes can achieve significantly higher ASE when compared to constant power schemes, almost reaching the upper bound of continuous power adaptation. Specifically, using just four rates and four power levels per rate results in a spectral efficiency that is within 1 dB of the continuous-rate continuous-power Shannon capacity. Further, the novel discrete transmission schemes reduce the probability of outage and are more robust against imperfect channel estimation and prediction.

In this paper we analyze the Opportunistic Round Robin (ORR) scheduling algorithm [1], [2]. This algorithm is able to exploit multiuser diversity (MUD) and at the same time provide short-term fairness between the users in a wireless cellular network. We analyze the spectral efficiency and the fairness for two scenarios. In the first scenario all the users have the same average carrier-to-noise ratios (CNR) and for the second scenario the users have different average CNRs. For the first scenario the absolute MUD is exploited while we exploit the so-called relative MUD between the users for the second scenario. The advantages and disadvantages of the different ORR implementations are highlighted by analyzing plots of our closed-form expressions.

The energy-efficient design of short-distance wireless communication systems requires the inclusion of circuit energy consumption in the system's total energy budget. We consider the design of link adaptation schemes in which circuit energy consumption is included in the total energy budget, in which a set of signal constellations of constant peak-to-average power ratio (PAPR) is used, and in which the transmitted power is kept constant whatever be the particular signal constellation in use. We show how the dimensionality of the associated non-linear optimisation problem can be reduced from N + 1 to one, where N denotes the number of available transmission schemes. These principles are then applied to a design example.

We investigate the influence of exact spherical wave propagation modeling and approximate plane wave propagation modeling on the properties of a pure line-of-sight 2 times 2 multiple-input multiple-output channel. As transmission distance increases, the properties of the true spherical wave model converge to the properties given by the more simple plane wave model. We present a new model evaluation tool based on an analysis of the rank and singular values of the channel matrix, which can be employed to find the region where spherical wave modeling is necessary. The derivation results in new exact analytical expressions for which of the two models that should be applied, and the results based on mutual information show that the spherical wave model should be applied in many practical scenarios, e.g. indoor WLAN scenarios, where plane wave modeling is most frequently used today

In this paper we investigate the performance of an adaptive coded modulation (ACM) system in single-input multiple-output Rayleigh fading channels with spatial correlation. The considered ACM system has a set of multi-dimensional trellis codes from which it can adaptively select the code best suited to the channel quality. The channel quality is tracked at the receiver by a predictor using a pilot-symbol-assisted modulation scheme. We optimize both the pilot spacing, and the power allocation to pilot and data symbols. The channel predictor is made optimal in the maximum a posteriori sense and the correlation to other subchannels is taken into account. A numerical example is given for flat Rayleigh fading subchannels with Jakes correlation profile.

In this paper, a performance analysis of a dual- branch switched diversity system operating on identically distributed Nakagami-m fading channels is presented. An adaptive coded modulation (ACM) scheme is employed to increase the spectral efficiency of the system. The ACM scheme consists of a set of multidimensional trellis codes originally designed for additive white Gaussian noise channels, where the codes are based on quadrature amplitude modulation (QAM) signal constellations of varying size. The performance is evaluated by assuming perfect channel knowledge at the receiver and instantaneous feedback of channel state information, conveyed from the receiver to the transmitter on a zero-error feedback channel. Both spatially uncorrelated and correlated antenna branches are considered. The optimal switching threshold in terms of maximizing the average spectral efficiency is identified in the case of uncorrelated antenna branches.

The Archimedes' spiral can be used as a 2:1 bandwidth reducing mapping in a joint source-channel coding (JSCC) system. The combined point of two iid Gaussian sources (the source space) is mapped, or approximated, onto a double Archimedes' spiral (the codebook), and the squared angle from the origin to the mapped point is transmitted as an analogue channel symbol (the channel space), e.g. PAM. It is shown that the total distortion of this JSCC system is minimised when the distortion contributions from the approximation noise and channel noise are equal. The given system produces a channel input distribution close to a Laplace probability density function (pdf) instead of the optimal Gaussian pdf. The loss when using this mismatched pdf is shown to be approximately equal to the relative entropy of the two pdf.

In wireless communications, bandwidth is a scarce resource. By employing link adaptation we achieve bandwidth-efficient wireless transmission schemes. We propose a variable-power transmission scheme for slowly varying flat-fading channels using a fixed number of codes. Assuming that capacity-achieving codes for AWGN channels are available, the proposed power adaptation scheme maximizes the average spectral efficiency (ASE) for any finite number N of available rates. We show that the power adapted transmission scheme, using just four different rates, achieves a spectral efficiency within 0.15 bits/s/Hz of the Shannon capacity for continuous rate and power adaptation. Further, when restricted to N optimally chosen rates, introducing power adaptation has significant ASE and outage probability gains over a constant power scheme

This paper describes a technique for realizing a high rank channel matrix in a line-of-sight (LOS) multiple-input-multiple-output (MIMO) transmission scenario. This is beneficial for systems which can not make use of the originally derived MIMO gain given by independent and identically distributed (i.i.d.) flat Rayleigh fading channels. Typical applications are fixed wireless access and radio relay systems. The technique is based on optimization of antenna placement in a uniform linear array. By introducing a new and more general geometrical model than that applied in earlier works, additional insight into the optimal design parameters is gained. A novel analysis of the sensitivity of the optimal design parameters is performed. The LOS transmission matrix is used in a Rician fading channel model, and performance is evaluated with respect to ergodic capacity, outage capacity, and effective degrees of freedom. The results show that even with some deviation from optimal design, the LOS MIMO case outperforms the i.i.d. Rayleigh case in terms of Shannon capacity.

We introduce a general adaptive coding scheme for Nakagami multipath fading channels. An instance of the coding scheme utilizes a set of 2L-dimensional (2L-D) trellis codes originally designed for additive white Gaussian noise (AWGN) channels. Any set of 2L-D trellis codes for AWGN channels can be used, Sets for which all codes can be generated by the same encoder and decoded by the same decoder are of particular interest. A feedback channel between the transmitter and receiver makes it possible to transmit at high spectral efficiencies under favorable channel conditions and respond to channel degradation through a smooth reduction of the spectral efficiency. We develop a general technique to determine the average spectral efficiency of the coding scheme for any set of 2L-D trellis codes. As an illustrative example, we calculate the average spectral efficiency of an adaptive codec utilizing eight 4-D trellis codes. The example codec is based on the International Telecommunications Union's ITU-T V.34 modem standard.

The performance of several decorrelating transforms is evaluated in the JPEG-2000 baseline system. The transforms considered are based on uniform parallel 2-channel and 8-channel filter banks and discrete cosine transform (DCT) building blocks. Through the analysis of lossy compression results, a system employing a combination of 8- channel and 2-channel filter banks is found to perform best overall. Also, the performance of several reversible transforms is evaluated in the same coding framework. Based on lossy and lossless compression results, a reversible version of the Cohen-Daubechies-Feauveau (2,2) wavelet transform was found to be most effective.

The paper presents an improved collage theorem, valid for a class of signal mappings called affine blockwise average (ABA) mappings. The ABA structure is exploited to form a bound depending on norms of collage error signals at several resolutions. Compared to previously published collage theorems, the new theorem provides a much tighter bound on the maximum distance between the original signal (real world image) and the decoder attractor, given the distance between the original and the "collage" optimized by the encoder. This is achieved without contractivity constraints on the ABA mapping parameters. Finally, an encoding method in which one attempts to minimize the upper bound directly is suggested.>

The present paper considers quantization of the parameters in a block-based fractal coding algorithm. First, the coding principle is explained. In contrast to more commonly used fractal coder variants, our method yields uncorrelated parameters within each image block. We analyze the statistical properties of the parameters in question, and suggest scalar quantization techniques based on these properties, as well as on a simple mathematical analysis of the effects of quantization. Finally, the quantization strategies suggested are tried out on a number of real world images. The results show that the loss of quality relative to using unquantized parameters is quite low.>

Consideration is given to modeling of arbitrary digital gray tone images as the fixed points of contractive transformations on the image space. The transformation is designed to exploit a form of image redundancy called piecewise self-similarity. Results from inner product space theory are used to optimize the transformation within a class of affine transformations. The resulting transformation is described by a small amount of information compared to the original image, and its piecewise self-similar fixed point, found by successively iterating the transformation from any initial image, is close to the original image. Results are improved compared to earlier results with this technique.>