We describe a basic single-user integrated sensing and communication (ISAC) system, considering a state-dependent discrete memoryless channel (DMC) with independent and identically distributed (iid) state sequences that are independent of the input sequence. Furthermore, we assume that no feedback is present and no state information is available to either the transmitter or the receiver. We derive the highest transmission rates achievable for our channel under a given distortion constraint, for three different receiver schemes: simultaneous decoding and estimation, decoding before estimation, and estimation before decoding. The state estimator is based on the idea of coded sensing, i.e., it uses a lossy source coding codebook to determine the estimate of the state sequence. The results hint towards a trade-off among the performance limits of such ISAC systems.

Low-resolution transceivers are being considered for millimeter-wave and higher frequency communications because of their simplicity and low power consumption. However, the non-linearities introduced by low-resolution digital-to-analog con- verters at the transmitters can cause significant out-of-band emissions since traditional bandwidth-limited pulse-shaping is not generally available. We model the performance of a low- resolution transmitter in terms of its spectral efficiency under out- of-band emission constraints. We show that the spectral efficiency can increase linearly with the symbol rate while satisfying out- of-band constraint. This implies that in order to achieve a given spectral efficiency under the bandwidth constraint, the symbol rate of the transmitter should be larger than a threshold. We derive an upper bound on this threshold.

We provide a mutual information lower bound that can be used to analyze the effect of training in models with unknown parameters. For large-scale systems, we show that this bound can be calculated using the difference between two derivatives of a conditional entropy function. We provide a step-by-step process for computing the bound, and apply the steps to a quantized large-scale multiple-antenna wireless communication system with an unknown channel. Numerical results demonstrate the interplay between quantization and training.

In the past few years, unmanned aerial vehicles (UAVs) have drastically increased in popularity both from consumer and industry perspectives. A key component towards enabling the widespread usage of UAVs is the ability to stay in near-constant communication with the drone for command and control and conveying relevant instrumentation. The usage of cellular technology, namely LTE, seems to be a natural fit for addressing coverage and Line of Sight (LoS) issues. However, there is a relative dearth of data, specifically open source data that explores key performance aspects of cellular at altitudes typically envisioned for commercial UAV operation. The key contribution of this paper is to analyze data taken from numerous drone flights that include varying altitudes, locations, and multiple cellular carriers as recorded in a medium-sized Midwestern city. Further, we offer our data as an open-source repository for the community offering multiple vantage points for the various runs including the operating system, chipset (through MobileInsight), drone instrumentation, and server-side packet captures as part of the recorded data streams.

We analyze the channel capacity of a system with a large number of one-bit transceivers in a classical Rayleigh environment with perfect channel information at the receiver. With M transmitters and N =αM receivers, we derive an expression of the capacity per transmitter C, where C ≤ min(1,α), as a function of a and signal-to-noise ratio (SNR) ρ, when M → ∞. We show that our expression is a good approximation for small M, and provide simple approximations of C for various ranges of α and ρ. We conclude that at high SNR, C reaches its upper limit of one only if α > 1.24. Expressions for determining when C “saturates” as a function of α and ρ are given.

To aggregate or not to aggregate, that is the question. Analog beamforming with phased arrays is a promising technique for 5G wireless communication in millimeter wave bands. However, beam squint degrades the performance of analog beamforming for wideband systems with a large number of antennas, because the array response varies with frequency. In this paper, we show that carrier aggregation for phased-array analog beamforming should take beam squint into consideration. Specifically, we study the optimal beam alignment to maximize channel capacity, and demonstrate that, with sufficient band separation, focusing on only one band outperforms carrier aggregation. Approximations are developed for a system with two bands to determine the critical values of system parameters like band separation, angle of arrival, and signal-to-noise ratio beyond which it is preferable not to aggregate.

Analog beamforming with phased arrays is a promising technique for 5G wireless communication in millimeter wave bands. A beam focuses on a small range of angles of arrival or departure and corresponds to a set of fixed phase shifts across frequency due to practical hardware constraints. In switched beamforming, a discrete codebook consisting of multiple beams is used to cover a larger angle range. However, for sufficiently large bandwidth, the gain provided by the phased array is frequency dependent even if the radiation pattern of the antenna elements is frequency independent, an effect called beam squint. This paper shows that the beam squint reduces channel capacity of a uniform linear array (ULA). The beamforming codebook is designed to compensate for the beam squint by imposing a channel capacity constraint. For example, our codebook design algorithm can improve the channel capacity by 17.8% for a ULA with 64 antennas operating at bandwidth of 2.5 GHz and carrier frequency of 73 GHz. Analysis and numerical examples suggest that a denser codebook is required to compensate for the beam squint compared to the case without beam squint. Furthermore, the effect of beam squint is shown to increase as bandwidth increases, and the beam squint limits the bandwidth given the number of antennas in the array.

We consider an OFDM system in the presence of a frequency-hopping interferer. We derive the Shannon channel capacity of the system with perfect and partial channel state information at the receiver (CSIR), where partial CSIR corresponds to knowledge of which sub-carrier the interferer affects. We also estimate the mutual information of the system with no CSIR, from which we compute the SNR gains that CSIR obtains. The results show that partial CSIR achieves the majority of the potential SNR gain for a given performance level. We consequently design a peak energy detector to estimate the interfered sub- carrier for a practical system and test the performance of the estimator both as a function of the interference dwell time and as a function of the interference power. The results indicate that longer dwell times enable the estimator to approach the performance of a genie-aided system and that a trade-off for increasing interference power exists between ease of detection and harm caused by missed detections.

We formulate a model for intermittent communication that can capture bursty transmissions or a sporadically available channel, where in either case the receiver does not know a priori when the transmissions will occur. Focusing on the point-to-point case, we develop a decoding structure, decoding from pattern detection, and its achievable rate for such communication scenarios. Decoding from pattern detection first detects the locations of code word symbols and then uses them to decode. We introduce the concept of partial divergence and study some of its properties in order to obtain stronger achievability results. As the system becomes more intermittent, the achievable rates decrease due to the additional uncertainty about the positions of the code word symbols at the decoder. In addition, we provide upper bounds on the capacity of binary noiseless intermittent communication with the help of a genie-aided encoder and decoder. The upper bounds imply a tradeoff between the capacity and the intermittency rate of the communication system, even if the receive window scales linearly with the code word length.

Analog beamforming with phased arrays is a promising technique for 5G wireless communication at millimeter wave frequencies. Using a discrete codebook consisting of multiple analog beams, each beam focuses on a certain range of angles of arrival or departure and corresponds to a set of fixed phase shifts across frequency due to practical hardware considerations. However, for sufficiently large bandwidth, the gain provided by the phased array is actually frequency dependent, which is an effect called beam squint, and this effect occurs even if the radiation pattern of the antenna elements is frequency independent. This paper examines the nature of beam squint for a uniform linear array (ULA) and analyzes its impact on codebook design as a function of the number of antennas and system bandwidth normalized by the carrier frequency. The criterion for codebook design is to guarantee that each beam's minimum gain for a range of angles and for all frequencies in the wideband system exceeds a target threshold, for example 3 dB below the array's maximum gain. Analysis and numerical examples suggest that a denser codebook is required to compensate for beam squint. For example, 54% more beams are needed compared to a codebook design that ignores beam squint for a ULA with 32 antennas operating at a carrier frequency of 73 GHz and bandwidth of 2.5 GHz. Furthermore, beam squint with this design criterion limits the bandwidth or the number of antennas of the array if the other one is fixed.

We present a tracking algorithm to maintain the communication link between a base station (BS) and a mobile station (MS) in a millimeter wave (mmWave) communication system, where antenna arrays are used for beamforming in both the BS and MS. Downlink transmission is considered, and the tracking is performed at the MS as it moves relative to the BS. Specifically, we consider the case that the MS rotates quickly due to hand movement. The algorithm estimates the angle of arrival (AoA) by using variations in the radiation pattern of the beam as a function of this angle. Numerical results show that the algorithm achieves accurate beam alignment when the MS rotates in a wide range of angular speeds. For example, the algorithm can support angular speeds up to 800 degrees per second when tracking updates are available every 10 ms.

This paper describes two concepts for Multichannel Immediate Multiple Access (MIMA) radio architectures for Dedicated Short-Range Communications (DSRC). Based upon an orthogonal frequency-division multiplexing (OFDM) physical layer, MIMA allows receivers to listen to all seven channels allotted for DSRC in the 5.9 GHz band and allows transmitters to send messages in any subset of the seven DSRC channels. The multichannel accessibility of MIMA further provides higher data rate for various applications, such as In-Vehicle Infotainment. The MIMA architectures are also compatible with the IEEE 802.11p standard, that is, they can coexist with 802.11p transceivers. One MIMA concept can increase spectrum utilization by up to 21.4% beyond carrier aggregation alone by utilizing guard bands in between aggregated DSRC channels. Another MIMA concept is to separate synchronization from demodulation and decoding, allowing a receiver to operate synchronizers for multiple channels in parallel but demodulating and decoding only those channels that are active, and thereby significantly reduce the FPGA or digital chip resources in the receiver. A prototype of the MIMA architecture has been implemented using an advanced software defined radio (SDR) platform. Preliminary results from the prototypes demonstrate the multichannel accessibility of the physical layer.

We study coded modulation over point-to-point Gaussian channels with discrete inputs and finite blocklength using recent tools from information theory. We show that finite-length channel coding has quite a significant effect at low SNR, and we identify SNR values below which the coded modulation is “dispersion limited”. Unlike the infinite-length case, coded PSK outperforms coded QAM in this dispersion-limited regime, based upon analysis of i.i.d. random codes. At high SNR, we show that finite blocklength coding barely affects the performance so that uncoded modulation is essentially optimal, and we quantify the SNR values beyond which the modulation is “entropy-limited”.

Motivated by the growing application of multi-access networks with stringent delay constraints, we investigate the Gaussian multiple-access channel (MAC) in the finite blocklength regime. By applying central limit theorem (CLT) approximations to non-asymptotic information-spectrum inner bounds, we obtain second-order achievable rate regions for the Gaussian MAC with a positive average error probability and per-codeword power constraints. Our achievability results use spherical inputs uniformly distributed on the power shells, which lead to summations of dependent information random variables. However, we conduct the analysis through a convenient yet powerful form of the CLT, called the CLT for functions.

Time division multiple access (TDMA) is widely considered to be a practical multi-access communication scheme that can achieve the highest possible sum-rate with appropriate power allocation. Exploring a Gaussian multiple access channel, we show that this result does not carry over to second-order coding rates. In particular, as the number of users grows, the cost of using TDMA is significant relative to the largest known achievable second-order sum-rate for the Gaussian MAC. The latter sum-rate is established by a random coding argument with non-i.i.d. spherical inputs, which is conveniently analyzed via a central limit theorem (CLT) for functions.

We formulate a model for intermittent multi-access communication for two users that captures the bursty transmission of the codeword symbols for each user and the possible asynchronism between the receiver and the transmitters as well as between the transmitters themselves. By making different assumptions for the intermittent process, we specialize the system to a random access system with or without collisions. For each model, we characterize the performance of the system in terms of achievable rate regions. The intermittency of the system comes with a significant cost in our achievable schemes.

In this paper, we investigate the effect of partial channel state information on the achievable secure communication rates and secret-key generation rates over ergodic fading channels. In particular, we establish the strong secret-key capacity as well as lower bounds for the strong secrecy capacity of ergodic and block-ergodic fading channels with partial Channel State Information at the Transmitter(CSIT). Our analysis sheds light on the usefulness of CSIT to harness the benefits of fading for secrecy and allows us to quantify the penalty incurred by the lack of full CSIT. In particular, we numerically illustrate situations in which little CSIT is required to recover most of the benefits of fading and in which the legitimate terminals have an incentive to precisely characterize their channel.

We analyze physical-layer security based on the premise that the coding mechanism for secrecy over noisy channels is tied to the notion of channel resolvability. Instead of considering capacity-based constructions, which associate to each message a subcode that operates just below the capacity of the eavesdropper's channel, we consider channel-resolvability-based constructions, which associate to each message a subcode that operates just above the resolvability of the eavesdropper's channel. Building upon the work of Csiszár and Hayashi, we provide further evidence that channel resolvability is a powerful and versatile coding mechanism for secrecy by developing results that hold for strong secrecy metrics and arbitrary channels. Specifically, we show that at least for symmetric wiretap channels, random capacity-based constructions fail to achieve the strong secrecy capacity, while channel-resolvability-based constructions achieve it. We then leverage channel resolvability to establish the secrecy-capacity region of arbitrary broadcast channels with confidential messages and a cost constraint for strong secrecy metrics. Finally, we specialize our results to study the secrecy capacity of wireless channels with perfect channel state information (CSI), mixed channels, and compound channels with receiver CSI, as well as the secret-key capacity of source models for secret-key agreement. By tying secrecy to channel resolvability, we obtain achievable rates for strong secrecy metrics with simple proofs.

The reduction in both user and control plane latency is a major goal for next generation (4G) cellular networks, specifically the Long Term Evolution-Advanced (LTE-A) standard. At the same time, relay stations, which introduce additional latency into transmissions, are seen as a potential means to improve cell spectral efficiency and coverage. This paper extends a number of existing relaying schemes to the case where a stricter latency constraint is applied. These low latency schemes are first evaluated for convolutional codes, for which they quickly approach the performance of full decoding at the relay with little additional latency over memoryless relaying. The schemes are then adapted for the turbo code in the LTE standard and shown to be preferable to full decoding and memoryless relaying for certain LTE-A relay types.

We consider secondary access policies with imperfect sensing in sensing-based dynamic spectrum access networks. Interference caused by both missed detections as well as the primary user's return to the channel during the secondary transmission are explored. We allow arbitrary distributions for the primary ON/OFF intervals and expand each interval into multiple sub-intervals to create a time-varying Markov model. From this perspective, efficient and well-developed trellis-based algorithms can be applied to obtain the secondary access policies. Simulation results demonstrate that the proposed policies achieve significant improvements in the system performance tradeoff relative to existing access policies that assume the sensing is perfect.

We formulate a model for intermittent communications that can capture bursty transmissions or a sporadically available channel, where in either case the receiver does not know a priori when the transmissions occur. Focusing on the point-to-point case, we develop two decoding schemes and their achievable rates for such communication scenarios. One scheme determines the transmitted codeword, and another scheme first locates the information symbols and then uses them to decode. The two-stage scheme leads to a higher achievable rate because it uses a generalization of the method of types in the first stage, which leads to a notion of partial divergence. We illustrate the results in the case of an intermittent binary symmetric channel.

Although practical communication networks employ coding schemes with blocklengths as low as several hundred symbols, classical information theoretic setups consider block-lengths approaching infinity. Building upon information spectrum concepts and recent work on channel dispersion, we develop a non-asymptotic inner bound on as well as a low-complexity, second-order achievable rate region for a discrete memoryless multiple access channel with a given finite blocklength and positive average error probability. Our bounds appear to capture essentially the same region as those of Tan and Kosut, but are less computationally complex because they require only the means and variances of the relevant mutual information random variables instead of their full covariance matrix.

Block Markov superposition encoding has been used on a number of channels to enable transmitter cooperation, including the decode-and-forward (DF) relaying scheme on the full-duplex relay channel. We analyze the error performance of DF with regular encoding and sliding window decoding as the window size of the decoder is allowed to grow. Specifically, we use Gallager's random coding exponent to analyze the behavior of DF in the finite block length regime where the error probability cannot be made arbitrarily small for a fixed rate and block length. Although using a larger decoding window may not result in a better achievable rate in the infinite block length regime, doing so for finite block lengths enables a higher rate of transmission for a given error probability. In particular, these rate enhancements can lead to a larger range of operating scenarios in which relaying can outperform direct transmission.

In this paper we develop and analyze low-complexity approaches called incremental multiple-input multiple-output (IMIMO) for exploiting multiple antennas for reliable wireless communications. The proposed schemes leverage consecutive uses of a single transmit antenna combined with automatic repeat request (ARQ) feedback. Unlike multiple-input multiple-output (MIMO) communications without feedback, the schemes we propose do not require a space-time encoder or decoder because they only use one transmit antenna at a time. We compare the performance of IMIMO schemes with the corresponding MIMO system without feedback using outage probability and average long-term throughput as metrics for comparison. These comparisons show that for relatively low rates IMIMO schemes have better performance than the corresponding MIMO system without feedback. For higher rates, MIMO with higher complexity performs better up to a certain signal-to-noise ratio, but beyond this threshold IMIMO schemes again have better performance.

We address the problem of power allocation to maximize ergodic capacity subject to multiple power constraints assuming that perfect causal channel state information (CSI) is available at both the transmitter and the receiver. We characterize the optimal power allocation subject to both long-term and short-term power constraints, which depends upon the ratio of the two power levels. Additionally, we find a suboptimal power allocation if the input power is subject to long-term and per-antenna power constraints. We characterize the conditions for which one power constraint dominates and the other can be ignored. Numerical results suggest that, for the Rayleigh fading case, a short-term power constraint that is larger than a long-term power constraint does not significantly impact the ergodic capacity of the channel. The effect of per-antenna power constraints is also explored for the case of Rayleigh fading through our numerical results.

In this paper, relaying and multi-cell MIMO transmission are investigated as approaches for improving resource reuse and more flexible organization of cellular networks. The analysis focuses on approaches for future cellular systems, which jointly exploit relaying and multi-cell MIMO transmission. Possible candidate approaches are identified, simplified for practical applications and evaluated using a system-level model from the European research project WINNER. Their achievable throughput is analyzed under practical constraints using three different normalization approaches: cost-normalization, energy-normalization, and joint cost-energy-normalization. It can be shown that the combined approach of relaying and multi-cell MIMO provides significant gains for the uplink communication. The selected approach exploits cooperative multi-cell MIMO processing between base stations and relay nodes, and uses a resource coordination technique on the links between relay nodes and user terminals. If a relay-based deployment is subject to a cost- and energy-normalization, multi-cell MIMO outperforms relaying with respect to achievable downlink throughput.

We consider several fading channel models for which we aim to maximize ergodic capacity assuming that channel state information (CSI) is available at both the receiver and the transmitter. We characterize the optimal power allocation structure in the single-input-single-output (SISO), multiple input-single-output (MISO), and multiple-input-multiple-output (MIMO) models subject to both long- and short-term power constraints. The optimal power policy in each of the channel models depends upon the ratio of the two power constraints and the average signal-to-noise-ratio (SNR) of the system. We characterize the conditions, for which the short-term power constraint can be eliminated without being violated in the optimal power policy. Numerical results suggest that for the Rayleigh fading case, a short-term power constraint that is larger than a long-term power constraint does not significantly impact the ergodic capacity of the channel.

We investigate channel code rates for communication of finite-dimensional analog sources over a multiple-antenna multiple access channel (MAC) so that the average end-to-end distortions are minimized. Our analysis uses the high-resolution quantization theory for the sources and the high-SNR diversity-multiplexing tradeoff for the MAC. We prove that carefully balanced channel coding rates, usually far from the boundary of the MAC capacity region, are necessary to achieve the optimal distortion exponent in a separated architecture. In particular, for the case of source vectors of equal dimension, we show that the channel interference from multiple users becomes crucial in characterizing the optimal channel coding rates if individual minimization of distortion for each user leads to a heavily loaded regime for the MAC.

This paper speculates on a perspective for studying overhead in communication systems that contrasts the traditional viewpoint that overhead is the “non-data” portion of transmissions. By viewing overhead as the cost of constraints imposed on a system, information-theoretic techniques can be used to obtain fundamental limits on overhead information, and multiple constraints lead to an intriguing chain rule for overhead. In principle, protocol overhead in practical implementations can then be benchmarked against these fundamental limits in order to identify opportunities for improvement. Several examples are discussed within this developing framework.

Design and analysis of cooperative communication schemes based upon modeling and simulation exist in large quantities in the research literature. Despite this fact, there have been relatively few efforts directed toward implementing and experimentally evaluating such schemes. Cooperative protocols have many components that make them challenging to implement in real-world radio architectures, and their expected gains are highly dependent on the network topology and RF environment in which they operate. As such, experimental work will be crucial in the transition of such schemes from conceptual proposals to next-generation wireless standards. This paper motivates such practical work, surveys existing efforts in the area, and offers future direction for architectural and experimental design.

Information embedding (IE) is the transmission of information within a host signal subject to a distortion constraint. There are two types of embedding methods, namely irreversible IE and reversible IE, depending upon whether or not the host, as well as the message, is recovered at the decoder. In irreversible IE, only the embedded message is recovered at the decoder, and in reversible IE, both the message and the host are recovered at the decoder. In this paper, combinations of irreversible and reversible IE in multiple access channels (MAC) and physically degraded broadcast channels (BC) are considered. In this paper, MAC IE in which separate encoders embed their messages into their host signals subject to distortion constraints is considered. The embedded signals from the two encoders are transmitted to a single decoder across a MAC. For the MAC IE model, the following three cases are considered: A) no host recovery at the decoder, B) lossless recovery of one host at the decoder, and C) lossless recovery of both hosts at the decoder. For the cases A and B, inner bounds on the respective capacity regions are developed. For the case C, inner and outer bounds on the capacity region are developed, and the capacity region is obtained if the hosts are independent. In this paper, BC IE in which two messages intended for separate decoders are embedded into a given host sequence by a single encoder subject to a distortion constraint is also considered. For the BC IE model, the following four cases are considered: A') lossless recovery of the host sequence at neither of the decoders, B') lossless recovery of the host sequence at only the better decoder, C') lossless recovery of the host sequence at both decoders, and D') lossless recovery of the host sequence at only the worse decoder. For cases A' and B', inner and outer bounds on the respective capacity regions are developed. For cases C' and D', the identical capacity regions are obtained.

In this paper, we consider a three-terminal state-dependent relay channel (RC) with the channel state noncausally available at only the relay. Such a model may be useful for designing cooperative wireless networks with some terminals equipped with cognition capabilities, i.e., the relay in our setup. In the discrete memoryless (DM) case, we establish lower and upper bounds on channel capacity. The lower bound is obtained by a coding scheme at the relay that uses a combination of codeword splitting, Gel'fand-Pinsker binning, and decode-and-forward (DF) relaying. The upper bound improves upon that obtained by assuming that the channel state is available at the source, the relay, and the destination. For the Gaussian case, we also derive lower and upper bounds on the capacity. The lower bound is obtained by a coding scheme at the relay that uses a combination of codeword splitting, generalized dirty paper coding (DPC), and DF relaying; the upper bound is also better than that obtained by assuming that the channel state is available at the source, the relay, and the destination. In the case of degraded Gaussian channels, the lower bound meets with the upper bound for some special cases, and, so, the capacity is obtained for these cases. Furthermore, in the Gaussian case, we also extend the results to the case in which the relay operates in a half-duplex mode.

Two driving goals for cognitive radio (CR) techniques are maximizing spectrum utilization and avoiding interference to primary users. In this paper, we deal with the CR concept for legacy primary links optimized for non-interference (singe user) environments. In this type of network, primary destinations are not able to deal with possible interference and a missed cognitive detection significantly reduces the system performance. The enhancement of the primary network with cooperative diversity in addition to the well-known diversity gain for the primary link improves the sensing ability of the system and protects the primary user from possible interference. Both Amplify-Forward and Decode-Forward (DF) cooperative schemes are studied for the problem under consideration and a new DF policy which introduces a cognitive relay behavior is investigated. The proposed technique provides CR benefits without complicated network modifications and seems to be an attractive solution for future legacy networks with flexibility limitations.

In this paper the interference channel is extended by additional relay nodes in order to investigate the influence of interference on the design and performance of relaying protocols. We introduce a framework in which the relay interference channel is decomposed into a cascade of individual interference channels with finite conference links at the transmitters. Each of these stages is able to implement interference cancellation and mitigation schemes such as dirty-paper and Han-Kobayashi coding. We discuss the dependencies between individual stages and propose specific approaches with reasonable complexity. Finally, we compare the performance of these protocols using a simplified model for the channel and network geometry of a mobile communications system. The results show that a reasonable choice is to coordinate the base-station to relay links using distributed dirty-paper coding and to mitigate interference on the relay to user link using Han-Kobayashi coding.

Compress-and-Forward is a protocol for transmission over relay networks in which the relay forwards a compressed version of the signal it observes. The compression method used by the relay is source coding with side information, i.e. Wyner-Ziv coding, since the destination can use the signal it receives directly from the source as side information. This paper addresses the case of a wireless relay network with orthogonal transmissions from the source and the relay terminals; we show that when the transmitters have no instantaneous channel state information the optimal compression parameters often make Wyner-Ziv coding reduce to conventional source compression, i.e. compression that does not take into account the side information available at the destination. This result simplifies the implementation of the CF protocol in the case we consider, since it shows that in several situations one can use more convenient compression methods without significant performance loss.

It is known that noiseless feedback does not increase the capacity of memoryless channels. However, such feedback can considerably increase the reliability or reduce the coding complexity of schemes that approach capacity. One might hope for the same to be (at least partially) true of noisy feedback. This paper develops a new class of coding schemes for additive white noise channels with feedback corrupted by additive white noise, focusing much of the results and discussion on the Gaussian case. These schemes are variants of the well-known Schalkwijk-Kailath (SK) coding scheme and are based upon simple techniques from stochastic approximation. Specifically, instead of the classic Robbins-Munro approach to stochastic approximation originally used in the SK scheme, we employ more recent techniques from Kushner. The resulting schemes enable a tradeoff between transmission rate and error performance in the presence of noisy feedback even as the number of iterations becomes large.

We consider a two-user state-dependent multiaccess channel in which only one of the encoders is informed, non-causally, of the channel states. Two independent messages are transmitted: a common message transmitted by both the informed and uninformed encoders, and an individual message transmitted by only the uninformed encoder. We derive inner and outer bounds on the capacity region of this model in the discrete memoryless case as well as the Gaussian case. Further, we show that the bounds for the Gaussian case are tight in some special cases.

We investigate the idea of providing information-theoretic security at the network and data link layers by exploiting the timing information resulting from queuing of packets between a source, an intended receiver, and other users in a network. Specifically, we consider the secure transmission of messages by encoding them onto the interarrival timing of packets that enter parallel queues. By leveraging recent results on the secrecy capacity of arbitrary wiretap channels, achievable secrecy rates are obtained. We also show that equivalent secrecy rates can be achieved using a deterministic encoding strategy, which provides an example contrasting the fact that for many memoryless channels a stochastic encoder is required to achieve non-zero secrecy rates.

This paper deals with protocol design for cognitive cooperative systems with many secondary users. Appropriate relaying improves the throughput of the primary users and can increase the transmission opportunities for the cognitive users. Based on different multi-access protocols, the schemes investigated enable relaying either between the primary user and a selected secondary user or between two selected secondary users. This collaboration can be a simple distributed multiple-input single-output transmission of the primary data or a simultaneous transmission of primary and secondary data using dirty-paper coding (DPC). The parametrization of DPC as well as its combination with opportunistic relay selection yields an interesting trade-off between the primary and the secondary performance which is investigated by theoretical and simulation results under the perspective of a desired primary throughput.

The goals of this demonstration are twofold. First, the demonstration seeks to provide an easy visualization of the effects multipath fading has on a wireless link and the benefits that cooperative communications can offer in mitigating this channel impairment. It does so by offering visual display of channel quality and receiver statistics. Second, it highlights the usefulness of software-defined radio (SDR) as a tool for wireless experimentation. This second objective is accomplished through the use of a custom SDR prototype within the cooperative demonstration.

This paper investigates downlink transmission over a quasi-static fading Gaussian broadcast channel (BC), to model delay-sensitive applications over slowly time-varying fading channels. System performance is characterized by the outage capacity region. In contrast to most previous work, here the problem is studied under the key assumption that the transmitter knows only the probability distributions of the fading coefficients, not their realizations. For scalar-input channels, two coding schemes are studied. The first scheme is called blind dirty paper coding (B-DPC), which utilizes a robustness property of dirty paper coding to perform precoding at the transmitter. The second scheme is called statistical superposition coding (S-SC), in which each receiver adaptively performs successive decoding with the process statistically governed by the realized fading. Both B-DPC and S-SC schemes achieve the outage capacity region, which dominates the outage rate region of time-sharing, irrespective of the particular fading distributions. The S-SC scheme can be extended to BCs with multiple transmit antennas.

This paper deals with protocol design for cognitive cooperative systems with many secondary users. In contrast with previous cognitive configurations, the channel model considered assumes a cluster of secondary users which perform both a sensing process for transmitting opportunities and can relay data for the primary user. Appropriate relaying improves the throughput of the primary users and can increase the transmission opportunities for the cognitive users. Based on different multi-access protocols, the schemes investigated enable relaying either between the primary user and a selected secondary user or between two selected secondary users. This collaboration can be a simple distributed multiple-input single-output transmission of the primary data or a simultaneous transmission of primary and secondary data using dirty-paper coding (DPC). The parametrization of DPC as well as its combination with opportunistic relay selection yields an interesting trade-off between the primary and the secondary performance which is investigated by theoretical and simulation results under the perspective of a desired primary throughput. The proposed protocols are studied from a networking point of view and the stable throughput for primary and secondary users is derived based on the principles of queueing theory.

In the above titled paper (ibid., vol. 6, no. 3, pp. 887-896, Mar. 07), a production error has occurred, and a correction should be made to replace Figures 1 and 2 with the figures presented here.

We investigate the amount of protocol information required for a communication network to meet an average delay constraint for the delivery of messages that arrive according to a Bernoulli random process. We obtain a lower bound on this overhead as a function of the arrival rate and average delay. Our model is a discretetime analog of the Poisson arrival process considered by Gallager, and we show that in the limit as slot duration goes to zero, Gallagerpsilas bound is recovered.

We consider a state-dependent full-duplex relay channel with the state of the channel non-causally available at only the relay. In the framework of cooperative wireless networks, some specific terminals can be equipped with cognition capabilities, i.e, the relay in our model. In the discrete memoryless (DM) case, we derive lower and upper bounds on channel capacity. The lower bound is obtained by a coding scheme at the relay that consists in a combination of codeword splitting, Gelpsilafand-Pinsker binning, and a decode-and-forward scheme. The upper bound is better than that obtained by assuming the availability of state at the source, the relay, and the destination. For the Gaussian case, we also derive lower and upper bounds on channel capacity. The lower bound, obtained by a coding scheme based on combination of codeword splitting and generalized dirty paper coding, is tight in some cases if the channel is physically degraded. The upper bound is also better than that obtained by assuming that the channel state is available at the source, the relay, and the destination.

This paper considers power and bandwidth allocation to maximize the end-to-end rate in a multihop wireless network. Assuming an orthogonal frequency division multiplexing (OFDM) system, we formulate an optimization problem for joint power and subcarrier allocation in a network with one destination and multiple sources and relays. We then focus on low-complexity algorithms for the special case of a multihop network with only one source. In particular, we develop an algorithm for a two-hop network based upon the observation that the optimal frequency allocation in a two-hop network has a two-band structure under certain conditions. For a network with more than two hops, we propose a greedy approach to subcarrier allocation. Simulation results suggest that the performance of the proposed algorithms closely follow the optimum performance. Moreover, our results suggest that more hops do not always improve the end-to-end spectral efficiency for frequency-selective fading channels.

This correspondence demonstrates the significant gains that multiple-access users can achieve fromsharinga single amplify-forward relay in slow-fading environments. The proposed protocol, namely, multiple-access amplify-forward (MAF), allows for a low-complexity relay and achieves the optimal diversity-multiplexing tradeoff (DMT) at high multiplexing gains. Analysis of the protocol further reveals that it outperforms both the compress-forward strategy at low multiplexing gains and the dynamic decode-forward protocol at high multiplexing gains. An interesting feature of the proposed protocol is that, at high multiplexing gains, it resembles a multiple-input single-output (MISO) system, and at low multiplexing gains, it provides each user with the same DMT as if there were no contention for the relay from the other users.

This paper applies spectral efficiency as a performance measure for routing schemes and considers how to obtain a good route in a wireless network. The objective for this study is to combine different perspectives from networking and information theory in the design of routing schemes. The problem of finding the optimum route with the maximum spectral efficiency is difficult to solve in a distributed fashion. Motivated by an information-theoretic analysis, this paper proposes two suboptimal alternatives, namely, the approximatelyideal- path routing (AIPR) scheme and the distributed spectrumefficient routing (DSER) scheme. AIPR finds a path to approximate an optimum regular path and requires location information. DSER is more amenable to distributed implementations based on the Bellman-Ford or Dijkstra's algorithms. The spectral efficiencies of AIPR and DSER for random networks approach that of nearest-neighbor routing in the low signal-to-noise ratio (SNR) regime and that of single-hop routing in the high SNR regime. In the moderate SNR regime, the spectral efficiency of DSER is up to twice that of nearest-neighbor or single-hop routing.

We consider a state-dependent multiple access channel p(y|x1, x2, s) whose output Y is controlled by the channel inputs x1and x2from two encoders and the channel state S. It is assumed that the channel state is known non-causally at one encoder, called the informed encoder. We derive the capacity region for the case of degraded messages in which the informed encoder knows the message of the uninformed encoder.

This paper studies a variant of the classical problem of "writing on dirty paper" in which the sum of the input and the interference, or dirt, is multiplied by a random variable that models resizing, known to the decoder but not to the encoder. The achievable rate of Costa's dirty paper coding (DPC) scheme is calculated and compared to the case of the decoder's also knowing the dirt. In the ergodic case, the corresponding rate loss vanishes asymptotically in the limits of both high and low signal-to-noise ratio (SNR), and is small at all finite SNR for typical distributions like Rayleigh, Rician, and Nakagami. In the quasi-static case, the DPC scheme is lossless at all SNR in terms of outage probability. Quasi-static fading broadcast channels (BC) without transmit channel state information (CSI) are investigated as an application of the robustness properties. It is shown that the DPC scheme leads to an outage achievable rate region that strictly dominates that of time division.

Cooperative communication systems using various relay strategies can achieve spatial diversity gains, enhance coverage, and potentially increase capacity. For the practically attractive decode-and-forward (DF) relay strategy, we derive a high-performance low-complexity coherent demodulator at the destination in the form of a weighted combiner. The weights are selected adaptively to account for the quality of both source-relay-destination and source-destination links. Analysis proves that the novel coherent demodulator can achieve the maximum possible diversity, regardless of the underlying constellation. Its error performance tightly bounds that of maximum-likelihood (ML) demodulation, which provably quantifies the diversity gain of ML detection with DF relaying. Simulations corroborate the analysis and compare the performance of the novel decoder with existing diversity-achieving strategies including analog amplify-and-forward and selective-relaying.

The thirty-four papers in this special issue are devoted to models, theories, and codes for relaying and cooperation in communication networks. The demand for large, more efficient, reliable, and cost effective communication networks is motivating new network architectures for cellular and wireless communications as well as cognitive radio and sensor networks.

This paper investigates the achievable information rate of phase-shift keying (PSK) over frequency nonselective Rayleigh and Rician fading channels without channel state information (CSI). The fading process exhibits general temporal correlation characterized by its spectral density function. We consider both discrete-time and continuous-time channels, and find their asymptotics at low signal-to-noise ratio (SNR). Compared to known capacity upper bounds under peak constraints, these asymptotics lead to negligible rate loss in the low-SNR regime for slowly time-varying fading channels. We further specialize to case studies of Gauss-Markov and Clarke's fading models

For fading channels without channel state information (CSI) at the transmitter or the receiver, fundamental challenges arise for realizing efficient communication, especially under stringent constraints on average and peak input powers. To mitigate these challenges, in this paper we investigate the benefits of spatial correlation among multiple transmit and receive antennas. Based upon asymptotic analyses, we first show that spatially correlated antennas lead to both multiplicative rate gain as well as peak power reduction, at no cost of additional transmit power. Then we turn to a simple communication scheme employing on-off signaling with hard-decision demodulation. For this low-complexity scheme, we demonstrate that most of the benefits promised by the asymptotic analyses are realizable

We consider information embedding (IE) in a degraded broadcast scenario in which two independent messages (w1, w2) are embedded into a given host sequence snunder the condition that the distortion between the embedded sequence xnand the host sequence satisfies a distortion constraint Delta. We consider four cases: A) lossless recovery of the host sequence at neither of the decoders, B) lossless recovery of the host sequence at the better decoder only, C) lossless recovery of the host sequence at both decoders, and D) lossless recovery of the host sequence at the worse decoder only. In all of the above cases, we consider decoding of the messages (w1, w2) at the better decoder and decoding of the message w2at the worse decoder. We develop inner and outer bounds for the broadcast IE capacity regions in cases A and B, and determine the broadcast IE capacity regions in cases C and D

The postal channel models a postal system in which letters, each consisting of a number of characters, are sometimes lost. We study the postal channel with variable-length letters and variable-length coding over letters, both with and without letter-by-letter feedback. Without allowing letter lengths to encode information, we examine one feedback strategy consisting of automatic repeat-request (ARQ) with exponentially increasing letter lengths. For this strategy we investigate an alternative notion of information rate per character, based upon the total, random number of characters required to convey the messages instead of its expectation. This information rate exhibits a phase transition in its convergence as the number of messages becomes large: if the letter lengths increase by a factor less than the inverse of the probability that a letter is lost, it converges to the channel capacity; otherwise, it converges to a number strictly larger than channel capacity. More generally, when we allow both the characters and the length of a letter to convey information, we compute the corresponding channel capacity with and without feedback, and find that it is twice the channel capacity of the original postal channel without allowing letter lengths to encode information

We compare the rate of a multiple-antenna relay channel to the capacity of multiple-antenna systems to characterize the cooperative capacity in different SNR regions. While it is known that in the asymptotic regime, at a high SNR or with a large number of cooperating nodes, cooperative systems lack full multiplexing gain, in this paper we consider cooperative capacity gain at moderate SNR with a fixed number of cooperating antennas. We show that up to a lower bound to an SNR threshold, a cooperative system performs at least as well as a MIMO system with isotropic inputs; whereas beyond an upper bound to the SNR threshold, the cooperative system is limited by its coordination costs, and the capacity is strictly less than that of a MIMO orthogonal channel. The SNR threshold depends on the network geometry (the power gain g between the source and relay) and the number of cooperating antennas M; when the relay is close to the source (g [unk] 1), the SNR threshold lower and upper bounds are approximately equal. As the cooperating nodes are closer, i.e., as g increases, the MIMO-gain region extends to a higher SNR. Whereas for a populous cluster, i.e., when M is large, the coordination-limited region sets in at a lower SNR.

The goal of this paper is to establish which practical routing schemes for wireless networks are most suitable for power-limited and bandwidth-limited communication regimes. We regard channel state information (CSI) at the receiver and point-to-point capacity-achieving codes for the additive white Gaussian noise (AWGN) channel as practical features, interference cancellation (IC) as possible, but less practical, and synchronous cooperation (CSI at the transmitters) as impractical. We consider a communication network with a single source node, a single destination node, and N-1 intermediate nodes placed equidistantly on a line between them. We analyze the minimum total transmit power needed to achieve a desired end-to-end rate for several schemes and demonstrate that multihop communication with spatial reuse performs very well in the power-limited regime, even without IC. However, within a class of schemes not performing IC, single-hop transmission (directly from source to destination) is more suitable for the bandwidth-limited regime, especially when higher spectral efficiencies are required. At such higher spectral efficiencies, the gap between single-hop and multihop can be closed by employing IC, and we present a scheme based upon backward decoding that can remove all interference from the multihop system with an arbitrarily small rate loss. This new scheme is also used to demonstrate that rates of O(logN) are achievable over linear wireless networks even without synchronous cooperation.

This correspondence investigates a noncoherent discrete-time memoryless Rayleigh-fading channel. A logarithmic transform converts it into an induced channel with additive noise that is independent of the channel input. From this perspective, it is natural and convenient for us to revisit several known results and gain new insights. In particular, we specify a class of simple, log-scale uniform channel input distributions that performs well for moderate to high signal-to-noise ratio (SNR). Furthermore, a continuous-amplitude log-scale uniform distribution is asymptotically capacity-achieving in the sense that the difference between the resulting mutual information and the channel capacity approaches zero as SNR becomes large. We also extend the induced additive-noise channel approach to memoryless multiple-antenna channels possibly with transmit, but without receive, spatial correlation.

This paper develops a general framework for maximum likelihood (ML) demodulation in cooperative wireless communication systems. Demodulators with piecewise-linear combining are proposed as an accurate approximation of the nonlinear ML detectors for coherent and noncoherent decode-and-forward (DF). The detectors with piecewise-linear combiner not only have certain implementation advantages over the nonlinear ML detectors, but also can lead to tight closed-form approximations for their error probabilities. High SNR approximations are derived based on the closed-form BER expressions. For noncoherent DF, the approximation suggests a different optimal location for the relay in DF than for the relay in amplify-and-forward (AF). A set of tight bounds of diversity order for coherent and noncoherent DF with multiple relays is also provided, and comparison between DF and AF suggests that DF with more than one relay loses about half of the diversity order of AF

We consider transmitting a source across a pair of independent, nonergodic channels with random states (e.g., slow-fading channels) so as to minimize the average distortion. The general problem is unsolved. Hence, we focus on comparing two commonly used source and channel encoding systems which correspond to exploiting diversity either at the physical layer through parallel channel coding or at the application layer through multiple description (MD) source coding. For on-off channel models, source coding diversity offers better performance. For channels with a continuous range of reception quality, we show the reverse is true. Specifically, we introduce a new figure of merit called the distortion exponent which measures how fast the average distortion decays with signal-to-noise ratio. For continuous-state models such as additive white Gaussian noise (AWGN) channels with multiplicative Rayleigh fading, optimal channel coding diversity at the physical layer is more efficient than source coding diversity at the application layer in that the former achieves a better distortion exponent. Finally, we consider a third decoding architecture: MD encoding with joint source-channel decoding. We show that this architecture achieves the same distortion exponent as systems with optimal channel coding diversity for continuous-state channels, and maintains the advantages of MD systems for on-off channels. Thus, the MD system with joint decoding achieves the best performance from among the three architectures considered, on both continuous-state and on-off channels.

This work develops a general framework for maximum likelihood (ML) demodulation in cooperative wireless systems with a demodulate-and-forward (DF) protocol at the relays. Although this general structure admits both coherent and noncoherent modulation, we analyze the performance of this demodulator mainly for noncoherent demodulation and compare it to existing results for coherent demodulation. The ML demodulator consists of a band of square-law devices followed by a nonlinear combiner. We develop an accurate approximation for this demodulator using a band of square-law devices followed by a piecewise-linear (PL) combiner. This approximation not only has certain implementation advantages, but also leads to a tight closed form approximation for the bit error rate (BER) of the ML demodulator. Based on this closed-form result, we derive a high signal-noise-ratio (SNR) approximation, that provides a simpler but tight approximation of the BER of the ML demodulator.

Low-delay decoding schemes based on window decoding are developed for the multiaccess channel with generalized feedback (MAC-GF). It is shown that window decoding sometimes incurs a rate loss as compared to backward decoding. Wireless cases are found for which the achievable rates with backward or window decoding give the capacity region.

This paper describes the source-channel coding diversity approaches for multimedia communication. The decision of which system to use should be based on both the benefits of a large distortion exponent as well cost, flexibility and ease of implementation

A wideband noncoherent multiantenna fading channel model in which the fading process exhibits both spatial and temporal correlation is analysed. By studying the derivative of mutual information at zero signal-to-noise ratio (SNR), the significant gain is achieved by increasing the number of transmit and receive antennas for MIMO channel.

We consider a wireless communication system with a single source node, a single destination node, and multiple relay nodes placed equidistantly between them. We limit our analysis to the case of coded TDMA multihop transmission, i.e., the nodes do not cooperate and do not try to access the channel simultaneously. Given a global constraint on bandwidth, we determine the number of hops that achieves a desired end-to-end rate with the least total transmission power. Furthermore, we examine how the optimum number of hops changes when an end-to-end delay constraint is introduced using the sphere-packing bound and computer simulations. The analysis demonstrates that the optimum number of hops depends on the end-to-end rate and the path-loss exponent. Specifically, we show the existence of an asymptotic per-link spectral efficiency, which is the preferred spectral efficiency in TDMA multihop transmission.

We develop and analyze low-complexity cooperative diversity protocols that combat fading induced by multipath propagation in wireless networks. The underlying techniques exploit space diversity available through cooperating terminals' relaying signals for one another. We outline several strategies employed by the cooperating radios, including fixed relaying schemes such as amplify-and-forward and decode-and-forward, selection relaying schemes that adapt based upon channel measurements between the cooperating terminals, and incremental relaying schemes that adapt based upon limited feedback from the destination terminal. We develop performance characterizations in terms of outage events and associated outage probabilities, which measure robustness of the transmissions to fading, focusing on the high signal-to-noise ratio (SNR) regime. Except for fixed decode-and-forward, all of our cooperative diversity protocols are efficient in the sense that they achieve full diversity (i.e., second-order diversity in the case of two terminals), and, moreover, are close to optimum (within 1.5 dB) in certain regimes. Thus, using distributed antennas, we can provide the powerful benefits of space diversity without need for physical arrays, though at a loss of spectral efficiency due to half-duplex operation and possibly at the cost of additional receive hardware. Applicable to any wireless setting, including cellular or ad hoc networks-wherever space constraints preclude the use of physical arrays-the performance characterizations reveal that large power or energy savings result from the use of these protocols.

Diversity schemes that exploit wireless channel variations in time, frequency, and space are an essential component for combating multipath fading in modern wireless communications systems. To evaluate performance and thereby design reliable and resource-efficient systems, designers require analytical tools that capture the salient, if not precise, characteristics of the fading channel model and diversity scheme employed. In this paper, we develop a simple and powerful way of characterizing performance of diversity schemes via limiting analysis of outage probabilities. As in other approaches to such an analysis, the two key parameters in our analysis are diversity order and coding gain, corresponding to the slope and intercept, respectively, in a plot of log-outage versus signal-to-noise ratio (SNR) in decibels (dB). Our approach allows for the characterization of a wide variety of diversity schemes operating over a broad class of fading channels, especially non-repetition diversity schemes such as parallel channel coding as well as multiuser diversity schemes such as cooperative diversity.

Diversity techniques often arise as appealing means for improving the performance of multimedia communication over certain types of channels with independent parallel components (e.g., multiple antennas, frequency bands or time slots). Diversity can be obtained by channel coding across parallel components at the physical layer. Alternatively, the physical layer ca present an interface to the parallel components as separate, independent links thus allowing the application layer to implement diversity in the form of multiple description source coding. We compare these two approaches in terms of average end-to-end distortion as a function of channel signal-to-noise ratio (SNR). When specialized to the case of an independent, identically distributed Gaussian source over Rayleigh fading channels, our results suggest that parallel channel coding at the physical layer is more efficient than independent channel coding combined with multiple description source coding. More generally, we provide intuitive guidelines for allowing system designers to identify which types of systems are preferable under different scenarios of practical interest.

We develop and analyze space-time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a manner that the destination terminal can average the fading, even though it is unknown a priori which terminals will be involved. In particular, a source initiates transmission to its destination, and many relays potentially receive the transmission. Those terminals that can fully decode the transmission utilize a space-time code to cooperatively relay to the destination. We demonstrate that these protocols achieve full spatial diversity in the number of cooperating terminals, not just the number of decoding relays, and can be used effectively for higher spectral efficiencies than repetition-based schemes. We discuss issues related to space-time code design for these protocols, emphasizing codes that readily allow for appealing distributed versions.

We develop and analyze space-time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a manner that the destination terminal can average the fading, even though it is unknown a priori which terminals will be involved. In particular, a source initiates transmission to its destination, and many relays potentially receive the transmission. Those terminals that can fully decode the transmission utilize a space-time code to cooperatively relay to the destination. We demonstrate that these protocols achieve full spatial diversity in the number of cooperating terminals, not just the number of decoding relays, and can be used effectively for higher spectral efficiencies than repetition-based schemes. We discuss issues related to space-time code design for these protocols, emphasizing codes that readily allow for appealing distributed versions.

We develop energy-efficient transmission protocols for wireless networks that exploit spatial diversity created by antenna sharing: coordinated transmission and/or processing by several distributed radios. We focus on single-user transmission and examine several possibilities for the strategy employed by the assisting radio, or relay, including decoding and forwarding as well as amplifying and forwarding. In each case, we develop receivers based upon maximum-likelihood and/or maximum signal-to-noise ratio criteria, relate their structures, and compare their bit-error probability performance by means of analysis and simulations. We cast single-hop and multihop routing into our framework for comparison purposes. All of our antenna sharing protocols offer diversity gains over single-hop and multihop transmission, and our results suggest that low-complexity amplifying and forwarding is energy-efficient in spite of noise amplification at the relay.

The problem of equalization for spread-response precoding systems based on minimum mean-square error (MMSE) estimates of the fading channel coefficients is considered. These systems are attractive, low complexity alternatives to the combination of interleaving and error-control coding for achieving time diversity in fading environments. To make the performance of these systems robust to channel estimation errors, we derive the linear equalizer at the receiver that maximizes the effective signal-to-noise-and-interference ratio (SNIR) subject to uncertainty in the channel measurements. We examine the bit-error rate performance and develop fixed and dynamic solutions to the associated problem of optimal power allocation between the data transmissions and channel measurements. The effectiveness of these algorithms is demonstrated through measurements obtained from an indoor wireless setting.