Ambient backscatter is is a relatively-recent technique being considered for communication from ultra-low power devices. Unlike typical backscatter applications where a dedicated reader-generated signal is used to power the tag, ambient backscatter uses readily available ambient signals such as FM radio, TV or WiFi signals. In this paper, we propose a simple, yet effective way to implement the receiver for a tag backscattering incident FM radio signals. The technique is based on treating the ambient FM as a carrier, which can be recovered using a phase-locked loop or another FM receiver. Coherent demodulation of the backscattered signal is then possible. Significant performance improvement can be expected over receivers that use energy-detection or other non-coherent demodulation techniques that are commonly used for ambient backscatter in the literature. We show that the FM radio signal can be recovered with a high fidelity even in the presence of the tag signal, with about 20-50 dB SINR in practical scenarios. Our results show up to 5 dB improvement in error performance over non-coherent reception.

The high popularity of LTE standard amongst the users and the service providers is resulting in an ever-increasing number of devices being included in LTE service architecture. This rate of inclusion with the higher demand of improved QOS/QOE with high mobility is resulting in an increment in consumption of energy by the LTE service architectures. High consumption of energy being critical to the environment due to its impact during generation of energy, consumption along with its effect on energy consuming devices has given rise to the demand of energy efficient algorithms that mitigate this rising energy demand by the architectures. We adopt an innovative approach in form of a Green Cellular Algorithm towards this issue of energy management and propose a testbed design in implementation and experimentation of the solution. We describe the approach towards designing the testbed and features peculiar to the implementation of the adopted green cellular algorithm using the testbed. Further, we also illustrate few basic scenarios to demonstrate the working of the algorithm on the testbed. Finally, we come up with future improvements in the testbed with respect to its ability to scale is size, implement different power efficiency algorithms with existing setup and also with technical improvements in the testbed.

Ultra wideband (UWB) radio technology has been shown to have tremendous potential to support certain Brain Computer Interface (BCI) applications. To implant UWB transmitters inside a human brain to transmit ECoG signals from the neurons in the brain (collected by bio-implantable electrodes) to stimulators residing on the spinal cord or on muscles at different parts of the body (non-invasive), almost sounds like a sci-fi story. In order to make this sci-fi dream a reality, many aspects of the problem needs to be addressed. In this paper, we attempt to study one such aspect. Specifically, we study the behavior of UWB transmissions through the human brain, primarily focusing on the behavior of the signal when it traverses through human blood in the brain before it can be received by the receiver planted on the surface of the human body (spinal cord, upper limbs, etc). We have performed in-depth numerical analysis through theoretical and experimental procedures which has helped us gain insight into the attenuation, delay and transmit power properties of the signal at different frequencies within the UWB spectrum. We present these results in this paper. So far, there are no channel models available for UWB transmissions inside the human body. Our work, is a step in that direction.

In the Wireless Body Area Network (WBAN), radio propagations from devices that are near or inside the human body are composite and unique contrasting with the different environments since the human body has a composite shape comprising of various tissues. Along these lines, channel models are unique in relation to the ones in alternate situations. We present a channel modelling of a situation imitating to the real one where multiple transmitters are placed in a human brain and a receiver is placed on the human skull. Results like Packet Collisions, Received Signal Level and Impulse Response were obtained through experiments that are presented in the results section.

With enormous growth in the telecommunication industry, energy efficiency has become a critical issue. Base stations and the core network account for a large amount of energy consumption today. Traditional energy saving techniques switch some base stations off completely during light loads to save energy. This creates problems for the backhaul network and also for quickly returning to full capacity when demand increases. In this paper, we propose novel cell zooming techniques to reduce energy consumption at base stations. With cell zooming, base stations dynamically adjust their coverage radius and hence their transmit powers based on user locations. The transmit power is set to the minimum required level depending on user locations, signal to interference and noise ratio (SINR) and quality of service (QoS) requirements of the users. Base stations are never completely switched off. Our simulations show that the proposed cell zooming algorithm reduces the energy consumption of base stations by up to 40% compared to traditional static-coverage-area base stations without compromising on the QoS requirements of any user in the cell.

WiMAX delivers Quality of Service (QoS) to users based on a pre-determined traffic classification model. We develop an auction framework to bid for allocating the resources based on the utilities and traffic demands. We classify the users into two categories Premium User who has a high priority access and Non premium user having low-priority access. In principle larger the bandwidth more resources WiMAX can support for the user traffic. We apply the concept of Incentive compatibility and use bidding mechanism to maximize the revenue and social welfare of the WiMAX networks. We have considered different cases to achieve this. First, Dependency of networks sharing the resources based on the concept of reduction to a maximum matching in weighted graphs. Second, Independency of networks with which it will share its resources. This is done by designing a max-min fairness algorithm with two different segments in a decision making process. a) A time dependent function that considers the time when packets wait in queues. b) A buffer utility function to consider buffer size in scheduling to prevent overflow and proportional fairness scheme to gives a fair share to users and maximize the social welfare and revenue.

Given the significant energy consumption in operating base stations (BSs), improving their energy efficiency is an important problem in cellular networks. To this end, this paper proposes a novel framework, called DCR (dynamic cell reconfiguration) that dynamically adjust the set of active BSs and user association according to user traffic demand for energy conservation. In order to overcome prohibitive computational complexity in finding an optimal solution, we take an approach to design simple yet effective algorithms. We demonstrate that the proposed framework is not only computationally efficient but also can achieve the performance close to the optimum solution from an exhaustive search. Through simulations based on a real dataset of BS topology and utilization, we show that DCR can yield about a 30-40% reduction compared to the conventional static scheme where all BSs are always turned on.

In this study, the authors investigate the performance of soft‐decision decoding of convolutional codes in receivers that employ square‐law detection. Traditionally, soft‐decision decoding has been considered only in coherent or differentially‐coherent receivers. Over the past few years, the emergence of ultra‐wideband (UWB) communication has brought energy detectors to prominence. In this study, the authors derive low‐complexity approximations for the log‐likelihood ratio (LLR) with a class of square‐law detectors in UWB radios. The authors then show that performance improvements, similar to those achievable in coherent detectors, can be obtained even with energy detectors when soft‐decisions are employed in a maximum‐likelihood decoding algorithm. The authors also investigate the complexity and accuracy of the proposed approximations when the LLR is computed using fixed point arithmetic. An expression for the bit error probability with soft‐decision decoding is derived. Several simulation results, including the error rate performance of hard‐ and soft‐decision decoding schemes with the exact and approximate LLR values, are presented.

In this study, authors propose structure to unit memory (UM) convolutional codes that greatly simplify their decoding when using sequential or suboptimal L ‐decoders. The multiscale structure proposed in this study preserves the word‐oriented nature of unit memory codes (UMCs), but allows for processing the code in blocks of sizes less than the memory of the code with non‐Viterbi‐type decoders. At one end of the multiscale structure are generic UMCs. At the other end are structured systematic UMCs that can be decoded with the same ease as conventional multimemory convolutional codes with sequential or L ‐decoders. As a special case, the authors show quick‐look parity check systematic codes of arbitrary rates that are better than previously known optimum minimum distance systematic convolutional codes. These codes are derived from block codes and the convolutional code can be decoded using the syndrome decoder of the underlying block code. The authors present simulation results and analysis to support the proposed multiscale UM convolutional codes.

This brief presents an improved layered space-time symbol detection algorithm for multiple-input multiple-output (MIMO) wireless systems. The proposed detection scheme utilises a different layer-ordering strategy than the so-called optimal ordering used in the conventional Bell Laboratories Layered Space-Time (BLAST) algorithm. To calculate the nulling vectors and their associated ordering, instead of using direct numerical techniques, the authors utilise a numerically stable iterative solution. It is shown that the performance of the proposed detector approaches closely that of an optimal maximum-likelihood detector at the expense of greater computational complexity compared with BLAST. Utilising the proposed parameterisable detector, one can trade off between the computational requirement and the error-rate performance.

The paper proposes a SINR based MAC layer protocol for multichannel ad-hoc networks. The protocol provides a distributed solution to a node pair that has to choose the “best” channel amongst the available `M' channels (M>;1). In this paper, we define “best channel selection” in terms of the least interference power measurement encountered on a particular channel by the receiving station throughout the entire duration of data exchange. Using Medium Access Control (MAC) layer mechanisms for message exchange between the nodes, our algorithm achieves not only interference mitigation but also solves the classical hidden and exposed terminal problems in wireless networks. Simulations performed on the NS-2 platform validates the throughput gain achieved by our algorithm in comparison to IEEE 802.11 MAC scheme alongside two other state-of-the-art multichannel MAC protocols.

Compressed video data is very sensitive to channel-induced errors and network losses. Most conventional unequal error protection techniques involve forward error correction codes of different rates or asymmetric signal constellations for data of different priorities. It is yet unknown if combining the above two techniques can further improve performance. In this paper, we investigate rate-compatible punctured convolutional (RCPC) codes concatenated with hierarchical QAM for H.264 encoded video sequences. We investigate system constraints and propose an optimization formulation to compute the optimal parameters of the proposed system under the given source significance information. An upper bound to the bit error rate of the proposed system is derived as a function of system parameters, including the code rate and geometry of the constellation. The example shown demonstrates system design for H.264 video, where PSNR improvement is observed.

In order to combat fading in an OFDM communications system, adaptive modulation techniques have been employed which can improve the performance. We propose that an artificial neural network (ANN) can be inserted in an OFDM system that would provide the information necessary to perform an adaptive modulation of the subcarriers. The performance of the system is evaluated in terms of symbol error probability. The results of our simulations allow us to validate our hypothesis.

In this paper, we describe a recently proposed bit-loading algorithm and a novel power-loading algorithm for block fading channels with channel state information (CSI) at the transmitter. We consider channels that offer a relatively small order of diversity, the so-called limited diversity fading channels. Limited diversity channels such as those encountered in indoor orthogonal frequency division multiplexing systems are characterized by the fact that achievable diversity orders are small and are limited by the channel and not by complexity of the code used. We first discuss a recently proposed analysis technique for the performance of bit-interleaved coded modulation on block fading channels. We then describe a bit-loading technique for maximizing the throughput at a fixed bit error probability. We also propose a new and simple power loading solution to minimize the bit error probability at a fixed rate. Lastly, we show comparative simulation results that corroborate the arguments presented in this paper.

In this study, the authors propose a novel technique for adaptive modulation over limited diversity fading channels with channel state information at the transmitter. Limited diversity channels such as those encountered in indoor orthogonal frequency division multiplexing systems are characterised by the fact that achievable diversity orders are limited by the channel and not by code-free distances. The authors first propose a novel analysis technique for the performance of coded modulation on limited diversity block fading channels with different modulation sets on each block. The authors then propose adaptive modulation techniques for maximising the throughput at a fixed bit error probability and also for minimising the bit error probability at a fixed rate. Lastly, the authors show simulation results that support the arguments presented in the paper.

A novel technique is described for distributed channel coding in wireless communication networks. The protocol is based on a block fading model of the multi-user uplink channel and on adapting multidimensional trellis coded modulation techniques to a coding theorem derived for the block fading channel. The coded modulation (CM) protocol is designed to optimise code performance, especially at high spectral efficiencies. The CM protocol is very simple to implement at the cooperating users. Complexity is completely transferred to the destination. The latency of the protocol is only one symbol. The CM protocol achieves full diversity order equal to the number of cooperating users and maximises coding gains by designing the code for the specific modulation used. We derive analytical results and present simulation results showing the benefits of CM protocol over other comparable schemes.

Coding with diversity is one of the keys to reliable wireless communication over fading channels. Adaptive modulation can provide additional performance improvement which may be significant when the channel diversity orders are small. In this letter, we propose adaptation algorithms for improving the power efficiency of coded orthogonal frequency division multiplexing (OFDM) on fading channels. We derive simple power-loading and bit-loading algorithms for achieving a fixed throughput and reliability with minimal transmitter power. We illustrate the performance of our schemes using simulations.

It has recently been recognized by many researchers that adaptive modulation is most effective when the channel diversity order is small. In this letter, we propose a simple adaptive modulation scheme for orthogonal frequency division multiplexing (OFDM) systems on channels that provide a small order of diversity. The proposed adaptation algorithm is based on a novel and very simple analytical formula we derive for the performance of BICM on block fading channels. Simulation results show that the derived analytical formula is very tight when the targeted bit error probability is small. OFDM systems on indoor channels provide small orders of diversity and form an ideal scenario for adaptation. In order to keep system complexity and feedback requirements at a minimum, we will consider symbol-level adaptive modulation wherein all the subcarriers in an OFDM symbol use the same modulation.

In this letter, we propose an extension to the ordered subcarrier selection algorithm (OSSA) for orthogonal frequency division multiplexing (OFDM) systems. The result is a simple algorithm for minimizing the bit error rate of the OFDM system at a fixed throughput. The proposed algorithm employs multiple modulations (non-uniform bit loading) within an OFDM symbol. However, unlike existing bit loading algorithms that have a very high computational complexity, the proposed algorithm is based only on the ordered statistics of the subcarrier gains and is consequently very simple. After ordering the subcarriers based on their gains, progressively higher order modulations are used with increasing gains. The key aspect here that greatly simplifies the algorithm is that the modulation used on a subcarrier depends only on the position of its gain in the ordered set and not on the actual values of the gains. We show an analytical approach for determining the parameters of the algorithm.

A novel technique for improving coding and diversity gains in orthogonal frequency division multiplexing (OFDM) systems is proposed. Multidimensional symbol design based on complex field codes with interleaving across frequency has been known for some time now. However, such symbols cannot be concatenated to convolutional codes owing to the prohibitive complexity of decoding. A novel way of designing multidimensional symbols that allow to concatenate them to convolutional codes while maintaining a low decoding complexity is shown. The proposed multidimensional symbols are based on tailbiting convolutional codes and the design of codes is discussed with desirable properties. Also the design of bit interleaved coded modulation-type and trellis-coded modulation-type codes over these multidimensional symbols is shown. Simulations show that the proposed coding scheme provides significant performance and/or complexity improvements over existing alternatives and also provides more degrees of freedom for channel-based link adaptation.

In this paper, power loading algorithms are presented for limited diversity fading channels with channel state information at the transmitter. Limited diversity channels are those that offer moderate levels of diversity (about 3-5) such as those encountered in orthogonal frequency division multiplexing (OFDM) based indoor wireless networks. We propose our ideas in the framework of a recently proposed coding approach for limited diversity channels although key aspects of the paper are valid for any coding scheme. We develop the optimal transmitter loading algorithm and also a low complexity suboptimal algorithm based on a linear objective function that maximizes the effective signal to noise ratio of the coded system. We compare the performances of different coding approaches with the proposed power allocation algorithms. Simulation results supporting the ideas presented in this paper are given.

In this paper, we propose a novel form of bit interleaved coded modulation (BICM) that we call generalized BICM (GBICM) for block fading channels. The achievable diversity order on block fading channels is limited by the channel itself and not by the code used. Conventional BICM attempts to maximize the Hamming free distance of the underlying convolutional code. Although this maximizes diversity on independently fading channels with ideal interleaving, its effect on block fading channels is not clear. In this paper, we analyze code performance on block fading channels and seek to optimize it by suitably modifying the BICM paradigm. The resulting GBICM system is just as simple and as flexible as BICM is when coding for different modulations and different kinds of channels. In fact, the same decoder can be used to decode both BICM and GBICM.We show code design principles and analysis techniques with examples. Simulation results supporting the arguments are shown.

In this paper, we present a novel concatenated trellis coded modulation (CTCM) scheme for limited diversity order fading channels. Examples for such channels include those encountered in indoor wireless networks like IEEE 802.11. It is first shown that when the diversity order afforded by the channel is fixed, bit interleaved coded modulation (BICM) is no longer the best way to encode. We then develop CTCM, which is superior to both BICM and conventional TCM of similar complexities. Unlike conventional TCM where convolutional codes are designed over modulated signal sets, CTCM has TCM concatenated to short length inner codes. Each trellis branch in the TCM now corresponds to a short block-code. We discuss design of good inner codes that allow for simple decoders. CTCM design incorporates useful features of both BICM and conventional TCM. Code design is explained with examples. Simulation results and information theoretic supporting the arguments are shown.

Recently, a coded modulation (CM) protocol was proposed for user cooperation diversity in wireless networks. The protocol was based on jointly encoding the data from all cooperating users into one code sequence. In this paper, further results relating to CM protocols are provided, including code analysis techniques. It is shown that tighter bounds are possible by merging a few successive trellis stages into a single bigger trellis with parallel transitions. Cooperation protocols depend critically on the performance over the channel between the cooperating users. Two adaptations of the CM protocol are shown that ensure robustness of the protocol for errors on the channel between the users. The single CM code is used in place of error correction codes anyway used by each user. So, CM based cooperation does not involve further constellation expansion. Hence, it is suitable for high spectral efficiencies also.

We propose a novel coded modulation (CM) protocol for user cooperation diversity in wireless networks. Unlike most existing protocols, the proposed scheme does not involve repetition. This translates to significant gains in terms of achievable rates. Hence, it is suitable for higher spectral efficiencies too. Each user transmits its own bits, along with bits of cooperating users, in every allotted symbol at appropriate positions on a specially labelled signal constellation. The scheme achieves full diversity order in the number of cooperating relays and obtains additional coding gains compared to repetition protocols. We show gains ranging from 2 dB to 3 dB over repetition protocols for cases involving two and three cooperating users. In its simplest form, the proposed scheme has a complexity at the relay equal to that of repetition protocols. Complexity at the base station, however, is increased.