Due to the shortage of IPv4 addresses, many hosts are currently assigned to a single IPv4 address by using one or a number of NAT devices. However, numerous NAT devices cannot be upgraded for executing 6to4 due to technical and/or economic reasons. Solutions depending on Double Network Address Translation 64 are a good way to utilise shared IP4 addressing. Mapping of address and port using translation (MAP-T) is a technique that accomplishes double translation on Border Relay (BR) and customer edge (CE) devices. IPv4 and IPv6 forwarding, IPv4 and IPv6 fragmentation functions, and NAT64 translation functions are used by MAP-T. This enables increasing numbers of IPv6 in both clients and servers in order to possess the best defence against certain attacks, such as routing loop attacks, spoofing attacks, denial-of-service attacks. We have here proposed some procedures for creating frameworks and sustaining secure IPv6 networks according to applications, environs and architecture.

With the emergence of the mission-critical Internet of Things applications, ultra-reliable low-latency communications are attracting a lot of attentions. Non-orthogonal multiple access (NOMA) with multiple-input multiple-output (MIMO) is one of the promising candidates to enhance connectivity, reliability, and latency performance of the emerging applications. In this paper, we derive a closed-form upper bound for the delay target violation probability in the downlink MIMO-NOMA, by applying stochastic network calculus to the Mellin transforms of service processes. A key contribution is that we prove that the infinite-length Mellin transforms resulting from the non-negligible interferences of NOMA are Cauchy convergent and can be asymptotically approached by a finite truncated binomial series in the closed form. By exploiting the asymptotically accurate truncated binomial series, another important contribution is that we identify the critical condition for the optimal power allocation of MIMO-NOMA to achieve consistent latency and reliability between the receivers. The condition is employed to minimize the total transmit power, given a latency and reliability requirement of the receivers. It is also used to prove that the minimal total transmit power needs to change linearly with the path losses, to maintain latency and reliability at the receivers. This enables the power allocation for mobile MIMO-NOMA receivers to be effectively tracked. The extensive simulations corroborate the accuracy and effectiveness of the proposed model and the identified critical condition.

High reliability and low latency, increasingly demanded by mission critical IoT applications, are the two key requirements for modern wireless communication systems. In this paper, we consider a battery-limited wireless machine type communication network where non-orthogonal multiple access (NOMA) is embedded to support massive connectivity. Hence, energy efficient NOMA transmission under statistical delay constraints is required to prolong the battery lifetime of the devices. We firstly derive the probabilistic upper bounds of the queueing delays of NOMA devices via the (min,×) stochastic network calculus. Then, we propose a transmit power optimization algorithm based the probabilistic delay bounds. Simulation results verify the tightness of the derived upper bound of the delay violation probability and thus the effectiveness of the proposed power control algorithm.

The explosive growth of user traffic brings a great pressure on evolved packet core (EPC) caused by huge numbers of emerging mobile intelligent applications. An EPC with good flexibility and scalability is required. In this paper, we proposed a virtualized and programmable EPC architecture (NOS-EPC) by leveraging the framework of not only stack (NOS) framework in order to satisfy the stringent requirements in beyond 5G (B5G) network. The global controller (GC) and the global network view (GNV) are established for the NOS-EPC. The control plane (C-Plane), the user plane (U-Plane) and the management plane (M-Plane) for the NOS-EPC, which are mutual and decoupled, are realized. NS3 based simulations are performed to verify the performance of the NOS-EPC. We compare the proposed NOS-EPC with different LTE solutions, including the LTE/EPC and software- defined network based EPC (SDN- EPC). The results show that the NOS-EPC can efficiently improve the EPC performance on the aspects of procedure duration and signaling overheads.

In future internet architectures, end-to-end (E2E) secured personal messaging is essential. So here an E2E user two-way authenticated double encrypted messaging architecture based on hybrid RSA for private messaging is proposed. Our P2P protocol works over TCP protocol for creating direct connections in between, with IPv4 broadcast options to discover peers on the same LAN. Our protocol implements perfect forward secrecy using Diffie-Hellman key exchange with renegotiation capability in every session with optimal asymmetric encryption padding and random salts. For making hybrid RSA with double encryption, in encryption level, main RSA is integrated with efficient RSA to give more statistical complexity. In the decryption process, the CRT is used for very high efficiency with integration with shared RSA. Our architecture also gives a hassle-free, secure, peer-to-peer, strong and reliable platform with E2E encryption for private messaging and it can also work with future internet architectures.

Efficient balancing of privacy and strong authentication in end-to-end (E2E) security constitutes a challenging task in the field of personal messaging. Since RSA is a ubiquitous approach, we here propose a hybrid RSA-based, highly efficient, reliable and strong personal full mesh networked messaging scheme. M-prime RSA and CRT-RSA with shared RSA makes our hybrid RSA decryption much more secure and efficient and protects our users with complete privacy. However, computational modular exponentiation complexity and partial key exposure vulnerability of RSA present two major obstacles. Low modular complexity and asymptotic very slow speed of decryption of RSA, with the ease and speed problem in encryption of RSA are also problems to be solved. Our hybrid RSA cipher resolves all of the above issues and provides protection against exploitation of multiplicative property and homomorphic property of RSA. Our full mesh networking scheme also ensures E2E encryption for all peers. So, our three-way authenticated hybrid RSA messaging scheme achieves a perfect balance of efficiency, security, authentication, reliability and privacy. Consequently, our scheme offers a smarter choice for private messaging in existing, as well as future, internet architectures.

Device-to-device (D2D) communication has been considered a promising solution for vehicle-to-vehicle (V2V) communication. In V2V underlay massive MIMO cellular networks, V2V has the potential to increase spectral efficiency (SE) by reusing cellular spectrum. However, the interference between cellular and V2V transmissions may be serious if not designed properly. In this paper, we first derive the analytical lower bounds on multi-antenna V2V and cellular SEs under both perfect and imperfect channel state information for maximum-ratio combining and zero-forcing detection. Using these lower bounds, performance analysis is given to provide more insights and guide practice. Then, we formulate a large-scale fading-based power control problem to guarantee the SE constraints of V2V pairs while maximizing the sum SE of cellular users. Moreover, the geometric programming technique is applied to solve the optimal power control problem. Numerical results show that the proposed SE-constrained power control scheme can greatly increase the reliability and achievable SE of V2V communications while the achievable sum SE is slightly degraded, compared with the fixed maximum power scheme.

We consider the cooperative rate splitting scheme in device-to-device (D2D) underlay cellular network to reduce the interference causing performance degradation of communication. At the transmitter end, the transmitted information is split into two parts: common information and private information. The common information is exchanged between base station and D2D transmitter, and encoded together. At the receiver end, the common information is firstly decoded jointly and cancelled out. In this paper, we derive the optimal power allocation factors for the common information and the private information to maximize the sum rate, just using the large-scale fading information which is known at the base station which can reduce the computational complexity greatly. The simulation results show that the proposed scheme achieves higher sum rate than traditional schemes.

Cloud radio access network (C-RAN) centralizes several baseband units to form a pool, which is the primary form of the wireless network virtualization. Some aspects of C-RAN are always developing, such as the processing capacity and multiple radio access technology (multi-RAT) convergence. In this paper, the Not Only Stack (NO Stack) framework, as a virtualization approach, is suggested to be employed in 5G radio access network (RAN). NO Stack is programmable, flexible, and sustainable, while adopting the mature virtualization technology to achieve a fully virtualized RAN (vRAN). With RAN slicing and network orchestration schemes, the baseband processing and storage resources could be sliced and orchestrated to realize the multi-RAT convergence and flexible reconfiguration. By reconstructing the dedicated and default bearer establishment procedure in long term evolution (LTE), NO Stack framework reduces the signaling and delaying respectively. Seen from the analysis and demonstration, the vRAN based on NO Stack can support multi-RAT convergence and flexible networking, as well as reduce the signaling and delay.

Sparse code multiple access (SCMA) is a competitive non-orthogonal multiple technique for 5G, which can accommodate more communication users by exploiting the multi-dimensional codewords. However, it is inflexible to meet the various demands of detection performance, or the various demands of computational complexity in real scenario. In this paper, we propose two simplified algorithms to deal with the problem, named GAMP-MPA and SIC-GAMP-MPA. These two algorithms are developed from the mainstream SCMA detector algorithm, message passing algorithm (MPA), and inspired by generalized approximate message passing (GAMP) as well as serial interference cancellation (SIC). The modified MPA benefits from the GAMP method since GAMP converts vector problems to scalar problems which provides higher computational efficiency and easier hardware implementation. Simulation results show that the GAMP- MPA achieves better performance than MPA with an acceptable extra complexity cost, and SIC-GAMP-MPA has significantly decreased complexity compared to MPA with similar performance. Particularly, the advantages of both GAMP-MPA and SIC-GAMP-MPA are more apparent in low signal-to-noise ratio (SNR) condition.

Soft errors induced by space radiation environments seriously influence the reliability of spacecrafts in space and satellite communications, especially with ever shrinking geometries, higher-density circuits, and power saving techniques. Most of the existing soft error mitigation methods depend on triple modular redundancy (TMR) or dual-modular redundancy (DMR) to the original design target directly, which enlarge the resource overhead dramatically. In this paper, the high level synthesis (HLS) is considered to help to reduce the resource consumptions of TMR or DMR. By the HLS on node sensitivity, all design resources can be classified into three types: sensitive submodules, semi-sensitive sub-modules, and insensitive submodules. TMR can be applied for sensitive sub-modules to provide the highest reliability, while gate sizing can be applied for semi-sensitive sub-modules, which can help to mitigate the soft errors and to minimize the overhead introduced by the fault-tolerant techniques efficiently. In order to verify the effectiveness of the above proposal, appropriate scheduling schemes combined with the HLS are performed to an FIR filter. By simulations it is shown that, with the reduction of area relative to TMR over 60% for the FIR design, the reliability can reach over 99.9%.

The massively dense distributed antenna system (md-DAS) with virtual cells (VCs) has drawn increasing interests recently. In this paper, we develop an energy-efficiency-oriented coordinated power allocation (PA) scheme considering the inter-VC interference in a downlink md-DAS. The problem can be formulated as a complicated non-convex fractional programming problem. To make it tractable, we recast the problem into quasi-concave fractional programming sub-problems, by applying successive Taylor expansion. Then we transform these subproblems into the equivalent convex ones in a subtractive-form based on fractional programming method. An iterative energy-efficient coordinated PA algorithm is finally proposed. Simulation results illustrate that the proposed scheme can offer a significant performance improvement over the existing methods.

This paper considers imperfect channel state information (CSI) in the downlink precoding of cellular multi-user large-scale distributed antenna system (DAS). Specifically, the uncertainty of channel estimation is mainly caused by the pilot reuse among users in adjacent cells. The phenomenon is termed as pilot contamination in a multi antenna system. Since the large-scale fading may vary from antenna to antenna, it's not easy to jointly estimate the channels from all antennas to a certain user. Instead, this paper only jointly estimates the downlink channels of the antennas at the same site, therefore with the same large-scale fading. Consequently, the channel estimation is executed in a distributed manner while the subsequent precoding is done in a centralized way. Based on the analysis of the properties of the DAS channel estimations, a multi-cell MMSE precoding scheme is proposed which aims to minimize the sum of intra- cell interference and the interference the cell pours to other cells. An approximation of the multi-cell MMSE precoding is further derived to reduce the computational complexity. Simulation results show significant performance gains over traditional singlecell precoding schemes.

Ultra dense network (UDN) is identified as one of the key enablers for 5G since it can provide ultra high spectral reuse factor exploiting proximal transmissions. By densifying the network infrastructure equipments, it's highly possible that each user will have one or more dedicated serving base station antennas, introducing the user-centric virtual cell paradigm. However, due to irregular deployment of large amount of base station antennas, the interference environment becomes rather complex, thus introducing severe interferences among different virtual cells. This paper focuses on the downlink transmission scheme in UDN where a large number of users and base station antennas are uniformly spread over a certain area. An interference graph is first created based on the large- scale fadings. Then, base station antennas and users in the virtual cells within the same maximal connected component are grouped together and merge into one new virtual cell cluster, where users are jointly served via zero-forcing beamforming. A multi-virtual-cell minimum mean square error precoding scheme is further proposed to mitigate the inter-cluster interference. Simulation results show that the proposed interference graph based virtual cell merging approach can attain the average user rate performance of the grouping scheme based on virtual cell overlapping with smaller virtual cell size and reduced signal processing complexity.

Dynamic channel assignment is an effective approach to decrease inter‐cell interference and improve link quality. Due to flat beam coverage property, link performance is degraded if conventional dynamic channel assignment schemes are directly employed in satellite network. To solve this problem, this study proposes the beam cooperation based dynamic channel assignment scheme, in which adjacent beams serve edge users cooperatively. Feature of feed sharing, channel model of satellite network, number of cooperative beams and combination method of the receiver are discussed in the proposed scheme. In addition, link quality restriction is applied to avoid drastically performance degradation in case of heavy traffic. Simulation results show that the proposed dynamic channel assignment scheme can effectively improve the average performance of users in the beam. Furthermore, the optimal antenna parameter for the proposed scheme is achieved by simulation.

Traditional macrocell networks are experiencing an upsurge of data traffic, and small-cells are deployed to help offload the traffic from macrocells. Given the massive deployment of small-cells in a macrocell, the aggregate power consumption of small-cells (though being low individually) can be larger than that of the macrocell. Compared to the macrocell base station (MBS) whose power consumption increases significantly with its traffic load, the power consumption of a small-cell base station (SBS) is relatively flat and independent of its load. To reduce the total power consumption of the heterogeneous networks (HetNets), we dynamically change the operating states (on and off) of the SBSs, while keeping the MBS on to avoid any service failure outside active small-cells. First, we consider that the wireless users are uniformly distributed in the network, and propose an optimal location-based operation scheme by gradually turning off the SBSs closer to the MBS. We then extend the operation problem to a more general case where users are nonuniformly distributed in the network. Although this problem is NP-hard, we propose a joint location and user density based operation scheme to achieve near-optimum (with less than 1% performance loss in our simulations) in polynomial time.

This paper proposes a MIMO system where the base station (BS) acquires quantized phase-only (PO) measurements of the complex baseband signal by our introduced stage-wised phase quantizer. PO-MIMO requires only one-bit ADCs for data sampling, so it successfully overcomes the ADC bottleneck that appears when the signal bandwidth is extremely wide. We construct a PO generalized approximate message passing (POG-AMP) algorithm for solving the linear mixing problem with quantized or unquantized phase measurements. POG-AMP has low computational complexity, exploits the signal prior statistical distribution, and handles the nonlinear distortions exerted on the measurements (e.g., losing magnitude and quantization). Then, POG-AMP is successfully applied to construct practical channel estimator and multiuser detector for PO-MIMO. Numerical results show that the POG-AMP estimator (POG-AMPE) and POG-AMP detector (POG-AMPD) are robust to the phase-quantization loss. POG-AMPE acquires high-quality channel side information at the receiver (CSIR), and POG-AMPD is robust to the CSIR errors when the BS antennas are massive enough. By introducing moderately more BS antennas, PO-MIMO with phase measurements even performs similarly to MIMO with full measurements containing both magnitude and phase. In order to maximize the transmit energy-efficiency, the lengths of the channel training sequences should be gradually increased with the increase of the channel coherence time. Antenna correlations at the BS degrade the convergence and bit-error rate performances of POG-AMPD, but can be handled by the analog spatial filtering technique.

Soft errors pose a reliability threat to modern electronic circuits. This makes protection against soft errors a requirement for many applications. Communications and signal processing systems are no exceptions to this trend. For some applications, an interesting option is to use algorithmic-based fault tolerance (ABFT) techniques that try to exploit the algorithmic properties to detect and correct errors. Signal processing and communication applications are well suited for ABFT. One example is fast Fourier transforms (FFTs) that are a key building block in many systems. Several protection schemes have been proposed to detect and correct errors in FFTs. Among those, probably the use of the Parseval or sum of squares check is the most widely known. In modern communication systems, it is increasingly common to find several blocks operating in parallel. Recently, a technique that exploits this fact to implement fault tolerance on parallel filters has been proposed. In this brief, this technique is first applied to protect FFTs. Then, two improved protection schemes that combine the use of error correction codes and Parseval checks are proposed and evaluated. The results show that the proposed schemes can further reduce the implementation cost of protection.

This paper proposes a multiuser MIMO system with both full measurements and one-bit magnitude observations, which are acquired by several linear inphase-and-quadrature (IQ) structured radio frequency (RF) chains and massive one-bit envelope chains, respectively. The total circuit power and cost are not increased significantly, since the added one-bit envelope chains have low power and low cost. Channel side information on the one-bit envelope chains is acquired by sharing the IQ-structured RF chains and executing a channel calibration operation. Two multiuser detectors are constructed based on the semidefinite relaxation (SDR) and approximate message passing (AMP). The one-bit magnitudes are interpreted as inequality constraints in the SDR detector, and exploited in a Bayesian manner by the AMP detector. Simulation results show that the one-bit magnitude measurements bring about high MIMO multiplexing and diversity gains, and decrease the transmission power. With the increase of the channel coherence time, more one-bit envelope chains are prone to be equipped, and one-bit magnitude-aided MIMO becomes more and more spectral-and-energy-efficient than the conventional MIMO.

In this paper, a new multi-cell MMSE detector is proposed for massive MIMO systems. Let K and B denote the number of users in each cell and the number of available pilot sequences in the network, respectively, with B = βK, where β ≥ 1 is called the pilot reuse factor. The novelty of the multi-cell MMSE detector is that it utilizes all B channel directions that can be estimated locally at a base station, so that intra-cell interference, parts of the inter-cell interference and the noise can all be actively suppressed, while conventional detectors only use the K intra-cell channels. Furthermore, in the large- system limit, a deterministic equivalent expression of the uplink SINR for the proposed multi-cell MMSE is derived. The expression is easy to compute and accounts for power control for the pilot and payload, imperfect channel estimation and arbitrary pilot allocation. Numerical results show that significant sum spectral efficiency gains can be obtained by the multi-cell MMSE over the conventional single-cell MMSE and the recent multi-cell ZF, and the gains become more significant as β and/or K increases. Furthermore, the deterministic equivalent is shown to be very accurate even for relatively small system dimensions.

In this paper, a new multi-cell MMSE precoder is proposed for massive MIMO systems. We consider a multi-cell network where each cell has K users and B orthogonal pilot sequences are available, with B = βK and β ≥ 1 being the pilot reuse factor over the network. In comparison with conventional single-cell precoding which only uses the K intra-cell channel estimates, the proposed multi-cell MMSE precoder utilizes all B channel directions that can be estimated locally at a base station, so that the transmission is designed spatially to suppress both parts of the inter-cell and intra-cell interference. To evaluate the performance, a large-scale approximation of the downlink SINR for the proposed multi-cell MMSE precoder is derived and the approximation is tight in the large-system limit. Power control for the pilot and payload, imperfect channel estimation and arbitrary pilot allocation are accounted for in our precoder. Numerical results show that the proposed multi-cell MMSE precoder achieves a significant sum spectral efficiency gain over the classical single-cell MMSE precoder and the gain increases as K or β grows. Compared with the recent M-ZF precoder, whose performance degrades drastically for a large K, our M-MMSE can always guarantee a high and stable performance. Moreover, the large-scale approximation is easy to compute and shown to be accurate even for small system dimensions.

This correspondence researches the multiuser detection (MUD) in a new massive MIMO system, where the base station (BS) acquires the quantized amplitude-only (AO) measurements of the complex baseband signals through the envelop detection and low-resolution analog-to-digital convertor (ADC) sampling. Cumbersome frequency mixers are removed and low-resolution ADCs can easily reach the Giga-sample-per-second (GSPS) rate, so massive AO-MIMO has low power and low cost, and is especially suitable for millimeter-wave (mmWave) communication. A practical multiuser detector is constructed based on the Wirtinger-flow (WF) gradient method for phase retrieval (PR), and the message passing de-quantization (MPDQ) algorithm for the quantized compressed sensing (CS). It iterates between the missing phase estimation and signal reconstruction, and involves only matrix-vector multiplication as its complex operation. Simulation results validate the effectiveness of the proposed detector, and show that massive AO-MIMO can even perform similarly as the classical massive MIMO by adopting relatively more BS antennas.

Full-duplex relaying (FDR) is an efficient technique to serve remote users with low power consumption, however, careful interference suppression is needed to mitigate self interference (SI) and multi-user interference (MUI). When multiple FDRs are employed, inter-relay interference (IRI) emerges and degrades system performance severely by consuming excessive transmit power. In this paper, distributed interference suppression in multiple full-duplex relays aided multiuser networks is investigated. A general model addressing all the three types of interference is established first. To minimize the total transmit power of the system, a distributed beamforming algorithm is proposed to jointly mitigate the three types of interference under individual user rate constraints. The algorithm requires only local information exchange at the relays, hence evidently reducing the signaling overhead in large-scale networks. Furthermore, theoretical proof for the algorithm's convergence is provided, and an upper bound for the iterative stepsize guaranteeing convergence is also derived. Numerical simulations validate effectiveness and stability of our proposal.

WiFi offloading helps serve ever-increasing data traffic in cellular networks and mitigate the network congestion. Yet it can only apply to cellular users within WiFi coverage. Recently, delayed WiFi offloading is proposed to exploit users' mobility to purposely travel to WiFi coverage for data offloading. Its successful implementation depends on users' willingness to delay ongoing cellular data services until entering WiFi coverage. This paper proposes an incentive mechanism to allow a network operator to optimally reward his users to participate in delayed WiFi offloading, so as to reduce the network congestion. We formulate the design problem as a two-stage Stackelberg game: in Stage I, the operator announces a uniform reward to users to delay their existing cellular services; and in Stage II, each user decides to join the delayed offloading or not, depending on the reward, the network congestion, and his estimation of waiting cost for WiFi connection. The operator and users may or may not know all users' mobility and waiting cost information; thus, we propose optimal reward mechanisms under various information availability scenarios. Interestingly, we show that the optimal reward does not always increase with the cellular traffic load, as the increased network congestion can also help motivate users to switch to WiFi networks.

This paper proposes a new large-scale antenna system (LSAS) where the base station (BS) is equipped with several classical radio-frequency (RF) chains but massive one-bit integrated information and energy receivers (Rxs). Multiple users with multiple antennas are served simultaneously. This new LSAS is much more energy efficient than massive MIMO because it requires much less classical power-hungry RF chains, and its massive integrated Rxs can harvest new energy. For the uplink multiuser detection (MUD), we develop a practical generalized approximate message passing detector (GAMPD), which exploits the signal prior probability distribution, and the hybrid BS measurements (full ones with both amplitudes and phases from the classical Rxs, and the one-bit amplitude measurements from the integrated Rxs) in a Bayesian manner. GAMPD involves matrix-vector multiplications, small-scale matrix inversions, and parallelized nonlinear operations, so it is suitable for hardware implementation. Our numerical results indicate that the proposed LSAS retains the advantages of massive MIMO, and can even perform similarly as the latter after introducing sufficient number of integrated Rxs.

In this paper, we research the multiuser detection (MUD) in a new massive MIMO with quantized phase-only (PO) measurements. Because the phase quantization can be implemented by one-bit ADCs, PO-MIMO overcomes the ADC bottleneck that appears when the signal bandwidth reaches multi-giga Hertz. However, the new problem is how to complete the uplink multiuser detection (MUD) based on the quantized PO measurements. In this paper, it is firstly solved by the sum-product-algorithm (SPA). Based on central limit theorem (CLT) and Taylor expansions, the SPA detector (SPAD) is simplified as a new PO generalized approximate message passing detector (POG-AMPD). POG-AMPD can exploit the quantized phase measurements and signal prior probability distribution in a Bayesian manner. It involves matrix-vector multiplications, and some parallelized non-linear operations, so it is suitable for hardware implementation. Numerical results indicate that POG-AMPD approaches to the maximum likelihood (ML) detection performance. By adopting moderately more BS antennas, massive PO-MIMO can even performs similarly as the conventional massive MIMO with full measurements.

Device-to-Device (D2D) underlay cellular communication has been recently considered as a popular paradigm to enhance system performance. In this paper, we study a power-allocation problem to maximize the system sum-rate while giving priority to cellular users (CUs), assuming that only large- scale fading information is known at the base station. Specifically, we give priority to CUs by introducing outage probability constraints. Further, we adopt the geometric programming technique to solve the optimal power-allocation problem. Numerical results show that the proposed outage- constrained power allocation scheme not only provides more reliable cellular communication but also improves the system sum-rate performance.

In uplink device-to-device (D2D) underlay cellular systems, massive multiple-input multiple-output (MIMO) seems promising as the large antenna array at the base station (BS) can nearly null the D2D-to- cellular interference. But the channel state information from all the users including D2D users to the BS is required to obtain the advantage. For the orthogonal channel training scheme, the pilot overhead becomes large with the number of users increasing, and constitutes a bottleneck for improvement of the system sum-throughput. In this paper, we propose pilot reuse (PR) for D2D underlay massive MIMO systems to reduce the pilot overhead and increase the system sum-throughput. Further, we develop a pilot scheduling algorithm under the criterion of minimizing the sum of mean square errors of channel estimation. Numerical results show that the proposed PR scheme can greatly increase the system sum-throughput at the price of slight degradation of cellular performance, compared to the conventional massive MIMO system.

This paper considers the error-detecting codes between two nodes. There are three transmissions between these two nodes: node A and node B. The first transmission can transmit one symbol within the alphabet {0, 1, ... , q1-1} from node A to node B; the second transmission can transmit one symbol within the alphabet {0, 1, ... , q2-1} from node B to node A; and the third transmission can transmit one symbol within the alphabet {0, 1, ... , q3-1} from node A to node B. One of the three transmissions may be erroneous. We prove that the maximum size of all 1-error-detecting codes over these three transmissions is min{q1, q2(q3-1)}.

A two-tier heterogeneous network, comprised of a macrocell underlaid with flexible and uncoordinated femtocell network, provides an economically viable way to improve indoor coverage, users' QoS and the capacity of the whole cellular network. However, mutual interference between macrocell and femtocell limits capacity and leads to the problem of coexistence. This paper proposes a game theoretical and decentralized spectrum negotiation framework to solve the above-mentioned problem. Macrocell and femtocell users have to reach a mutual satisfactory agreement on the partition of spectrum by making alternating offers to each other. By modeling the bargaining process as multi-stage dynamic game, we are able to obtain the equilibrium outcome. Theoretical and numerical analysis on negotiation results show that macrocell and femtocell can achieve a fair, efficient, and incentive compatible spectrum allocation via the proposed bilateral negotiation interactions.

Small cells deployed over the existing macrocell network reduce the access distance and thus offer an energy-efficient solution to provide high data rate coverage. However, dense deployment of small cells may cause energy waste under low load conditions. To cope with this issue, power saving techniques for small cell networks need to be carefully investigated. Invoking a sleep mode is one of the most promising techniques, which allows a small cell base station (SBS) without active users to enter a low power mode and switch to an active mode when required. When a user is within the coverages of several SBSs, the SBS with the best channel condition should be activated by comparing the channel fading from different SBSs to the user. Selecting the right SBS for an active user is challenging because the sleeping SBSs do not send or receive radio frequency signals for channel estimations. In this paper, we propose an energy efficient sleep mode activation scheme for small cell networks, in which the core network activates the sleeping SBS with the smallest large-scale channel fading to the active user. This scheme makes use of channel measurements in advance and adopts spacial interpolation to estimate the large-scale channel fading from sleeping SBSs to the active user. Simulation results show that the spacial interpolation can effectively estimate the large- scale channel fading, and the proposed sleep activation scheme can effectively save transmit power and hence improve the overall network energy- efficiency.

This paper studies the allocation of information flows in noiseless, memoryless communication networks in the presence of omniscient Byzantine adversary. In such networks, adversary may maliciously modify some edge-flows, and legitimate users should resort to network error correction strategies to transmit data reliably. Unlike prior papers, which focused on the capacities of the networks, we consider the expense of resources used by the flow. Hereby, this paper uses an optimization problem to define the concept of minimum cost network error correction flows. We provide a necessary and sufficient condition of feasibility of the allocation problem, and derive a cut-set outer bound on the feasible region. Using this cut-set bound, we can find the minimum cost network error correction flow in some instances. Moreover, we also consider the relationship between incoming edge-flows and outgoing edge-flows of a vertex. As for the directed acyclic graphs, we propose an algorithm to allocate the network error correction flow. This algorithm is with polynomial time complexity, and proves to be optimal when recoding at intermediate nodes is forbidden. Additionally, in order to justify the necessity of recoding at intermediate nodes, we analyze the benefit of intermediate recoding. On the one hand, we construct a series of instances to prove that intermediate recoding can bring enormous benefits in some networks. On the other hand, numerical analysis shows that the benefit is modest in small random graphs.

In distributed multilevel diversity coding, K correlated sources (each with K components) are encoded in a distributed manner such that, given the outputs from any α encoders, the decoder can reconstruct the first α components of each of the corresponding α sources. For this problem, the optimality of a multilayer Slepian-Wolf coding scheme based on binning and superposition is established when K ≤ 3. The same conclusion is shown to hold for general K under a certain symmetry condition, which generalizes a celebrated result by Yeung and Zhang.

Digital filters are widely used in signal processing and communication systems. In some cases, the reliability of those systems is critical, and fault tolerant filter implementations are needed. Over the years, many techniques that exploit the filters' structure and properties to achieve fault tolerance have been proposed. As technology scales, it enables more complex systems that incorporate many filters. In those complex systems, it is common that some of the filters operate in parallel, for example, by applying the same filter to different input signals. Recently, a simple technique that exploits the presence of parallel filters to achieve fault tolerance has been presented. In this brief, that idea is generalized to show that parallel filters can be protected using error correction codes (ECCs) in which each filter is the equivalent of a bit in a traditional ECC. This new scheme allows more efficient protection when the number of parallel filters is large. The technique is evaluated using a case study of parallel finite impulse response filters showing the effectiveness in terms of protection and implementation cost.

Channel measurements show that significant spatially non-wide-sense-stationary characteristics rise in massive MIMO channels. Notable parameter variations are experienced along the base station array, such as the average received energy at each antenna, and the directions of arrival of signals impinging on different parts of the array. In this paper, a new channel model is proposed to describe this spatial non-stationarity in massive MIMO channels by incorporating the concepts of partially visible clusters and wholly visible clusters. Furthermore, a closed-form expression of an upper bound on the ergodic sum capacity is derived for the new model, and the influence of the spatial non-stationarity on the sum capacity is analyzed. Analysis shows that for non-identically-and-independent-distributed (i.i.d.) Rayleigh fading channels, the non-stationarity benefits the sum capacity by bringing a more even spread of channel eigenvalues. Specifically, more partially visible clusters, smaller cluster visibility regions, and a larger antenna array can all help to yield a well-conditioned channel, and benefit the sum capacity. This shows the advantage of using a large antenna array in a non-i.i.d. channel: the sum capacity benefits not only from a higher array gain, but also from a more spatially non-stationary channel. Numerical results demonstrate our analysis and the tightness of the upper bound.

In this paper, we research the multiuser detection (MUD) in a new Spatial Modulation Multiple-Input-Multiple-Output (SM-MIMO) system, whose Base Station (BS) is equipped with massive Radio-Frequency (RF) chains with low-resolution Analog-to-Digital Convertors (ADCs), and the User Equipments (UEs) have multiple Transmit Antennas (TAs) but single RF chain. In the uplink, UEs transmit their data by the Cyclic-Prefix Single-Carrier (CP-SC) SM technique. The key is how to design practical MU detectors to handle the severely quantized measurements and antenna correlations. Coherent detection is focused, so a Least-Square (LS) channel estimator is designed to acquire the the channel side information (CSI) at the Receiver (CSIR). Then, we firstly solve the MUD problem by the Sum-Product-Algorithm (SPA) on a clustered factor graph (FG) whose variable nodes correspond to the transmitted vectors from the UEs. Next, based on the Central Limit Theorem (CLT) and Taylor expansions, the SPA detector (SPAD) is simplified as a new low-complexity Message Passing De-Quantization Detector (MPDQD), which exploits both the structured sparsity and prior probability distribution of the transmitted signal. By utilizing the clustering technique, damping mechanism, and Analog Spatial Filtering (ASF), the robustness of MPDQD is improved significantly. Simulation results show that MPDQD outperforms the linear detectors, works steadily under strong channel correlations, and even performs similarly as its counterpart in the un-quantized SM-MIMO.

In this work, we research the multiuser detection (MUD) in a new Single Carrier (SC) massive Spatial-Modulation-Multiple-Input-Multiple-Output (SM-MIMO) system, where the Base Station (BS) is equipped with massive antennas connecting to independent Radio-Frequency (RF) chains designed by low-resolution Analog-to-Digital Converters (ADCs). Different User Equipments (UEs) possess multiple Transmit Antennas (TAs) but only one RF chain, and transmit data-bits to the BS by Cyclic-Prefix Single-Carrier (CP-SC) SM. We construct a new Message Passing De-Quantization Detector (MPDQD) based on the MPDQ algorithm in Compressed Sensing (CS). MPDQD exploits both the special structures (e.g., sparsity) and prior probability distribution of the transmitted signal, so it reaches superior detection performances. It involves the parallelized matrix-vector multiplication as the most complex operation, so it has low complexity and is suitable for hardware implementation. Simulation results show that MPDQD outperforms the linear detectors, and can approach the performance of the un-quantized system even when ADC resolution is low (e.g., 4bits).

In large-scale Multiple Input Multiple Output (MIMO), the number of Base Station (BS) antennas reaches tens even hundreds. If so many radio frequency front-ends adopt the classical receivers, their cost and power consumption during the receiving mode would increase quickly. Consequently, we exploit one-bit Analog Digital Convertor (ADC) to design low-cost and low-power software defined radio receivers for the BS. However, the new problem is how the BS fulfills Multiuser Detection (MUD) based on the one-bit baseband data. Based on the Message Passing De-Quantization (MPDQ) algorithm, an iterative multiuser detector is constructed. Its convergence properties is analyzed by the State Evolution (SE), and then its complexity is proved to be one order of magnitude smaller than that of the Minimum Mean Square Error (MMSE) detector. Simulation results show that the proposed detector outperforms MMSE. Finally, the proposed detector with matrix-vector multiplications is suitable for hardware implementation.

In large-scale Multiple-Input-Multiple-Output, the Base Station (BS) is equipped with a large-size antenna array containing tens even hundreds Radio Frequency channels. If so many RF front-ends adopt the classical receivers, their cost and power consumption during the receiving mode would increase quickly. Therefore, we exploit low-resolution Analog-to-Digital-Convertor to design low-power and low-cost software defined radio receivers for the BS. However, the new problem is how the BS fulfills channel estimation and Multiuser Detection (MUD) under low-resolution quantization. In this paper, first, least square method is used for channel estimation, and a robust Maximum Likelihood (ML) MUD problem is constructed to take into account the channel estimation errors. Second, an iterative multiuser detector is constructed by relaxing the ML MUD problem as a convex optimization problem and then solving the convex problem through the nonmonotone spectral projected gradient method. Compared with the Minimum Mean Square Error (MMSE) detector, the proposed detector has lower computational complexity, and is more suitable for hardware implementation. Simulation results show that it also outperforms MMSE.

This paper considers interactive transmissions in the presence of omniscient Byzantine attacks. Unlike prior papers, it is assumed that the number of transmissions, the number of erroneous transmissions therein, and the direction of each transmission are predetermined. Besides, the size of the alphabet in each transmission is unequal and predefined. Using these transmissions, two nodes communicate interactively to send a message. In this model, both attack strategies and coding bounds are considered. Although the codebook can not fully describe the interactive code, we still assert the existence of successful attack strategies according to the relations between codewords in the codebook. Furthermore, to ensure that the code is able to detect or correct a given number of transmission errors, upper bounds on the size of code are derived. Finally, the tightness of the bounds is discussed.

This paper presents an analytical study on the outage performance of cognitive decode-and-forward (DF) two-way relaying networks with underlay spectrum sharing. The bidirectional protocol, i.e., two time-slot multiple access broadcast (MABC) and three time-slot time division broadcast (TDBC), are considered. We propose a definition of outage probability by jointly considering outage events in the whole transmission process and the exact outage probability expressions are given. For both the protocols, the dependence among the received signal- to-noise ratios (SNRs) in the broadcast phase is introduced due to the interference power constraint. The joint probability of the received SNRs is derived. Based on that, the closed-form solutions to outage probability for the two protocols are obtained. The theoretical analysis is verified by Monte-Carlo simulations. Results demonstrate that MABC can achieve better outage performance through optimal interference power distribution between the two secondary users.

Repeat transmission of hotspot traffics results in great waste of energy and bandwidth in wireless network, for the communication of current network is content careless. To address this issue, a novel content aware transmission schema named CASoRT System was put forward in our previous research to reduce wireless resource waste by the benefit of broadcast. In this paper, we propose a K neighbors collaborative filtering prediction method to forecast the request of hotspot traffics, which will be broadcasted by CASoRT. Firstly, we introduce the traditional prediction methods and describe the framework of our job. Then, we deliver the expression of our method in formulation, and discuss the time complexity in quantitative analysis. At last, our method is validated by simulation, and the results demonstrate that the new schema can potentially lead to 20% deduction compared with the unicast schema in hotspot traffic transmission. And the results also show that our method reduces 25% prediction time than traditional methods, but with the same performance in saving wireless resources.

In large-scale Multiple-Input-Multiple-Output (MIMO) downlink, one state-of-the-art precoder significantly reduces the Peak-to-Average Power Ratio (PAPR) of the emitted signals from the Base Station (BS) antennas through minimizing the ℓ∞-norm of the precoded signals (generated by the precoder and transmitted by the BS RF frontends). In this paper, its computational complexity is analyzed based on the random matrix theory, and its two variants are constructed as follows. First, the ℓ∞-norm is approximated by a high order ℓp-norm (e.g. ℓ16), and then the downlink precoding problem is solved by classical Gradient Descent (GD) method. Second, the ℓ∞-norm is removed directly after additional box constraints are exerted on the elements of the precoded signals. Then the precoding problem is solved by spectral GD algorithm. Simulation results show that the above three convex-optimization based precoders can reduces the PAPR by more than 11.5dB compared to conventional precoding schemes.

In this paper, an iterative multiuser detector is proposed for uplink large-scale Multiple Input Multiple Output (MIMO). It is developed based on the Generalized Approximate Message Passing (GAMP) algorithm, and its convergence properties are analyzed by a one-dimensional iteration termed as State Evolution (SE). The SE analysis proves that the complexity of the GAMP detector (GAMPd) is one order of magnitude smaller than that of the Minimum Mean Square Error (MMSE) detector. Simulation results show the GAMPd performs similarly to MMSE at least, and even outperforms the latter when the number of BS antennas is not much larger than the number of users. In addition, the GAMPd with matrix-vector multiplications is suitable for hardware implementation.

As energy consumption reduction has been an important concern for the wireless industry, energy-efficient communications is of prime interest for future broadband networks. In this paper, we study the energy efficiency of relay-assisted cellular networks using tools from stochastic geometry. We first derive the coverage probability for the macro base station (MBS) to user (UE), the MBS to relay station (RS), and the RS to UE links, and then we model the power consumption of MBSs and RSs. Based on the analytical model and expressions, the energy efficiency of relay-assisted cellular networks is then evaluated and is shown to be strictly quasi-concave on the transmit power for the MBS to UE link or the RS to UE link. Numerical results also show that the energy efficiency first improves while it hits a ceiling as the MBS density increases.

Satellite and terrestrial integrated mobile communication systems (STICS) is proposed to secure communications services anytime and anywhere. In the case of natural disasters or special event, it is required for satellite systems to allocate the frequency resources to a specific area as much as possible. Dynamic channel assignment is one of the attractive solutions to achieve the flexible and efficient utilization of the frequency resources. Although dynamic channel assignment can increase the bandwidth per satellite cell, smaller frequency reuse factor results in larger inter-cell interference and the link quality degradation. To solve this problem, this paper proposes centralized dynamic channel assignment based on interference measurement with link quality threshold control for multi-beam mobile satellite communications networks. It also shows the performance evaluation results by computer simulations regarding the blocking rate and the link quality.

Approximate Message Passing (AMP) simplified from Loopy Belief Propagation (LBP), is an important algorithm for sparse signal reconstruction in Compressed Sensing (CS). To improve the performance of current AMP algorithms, a weighted-damped AMP algorithm (WDAMP) is derived from a weighted version of BP that adopt probability damping technique. Simulation results show that WDAMP outperforms normal AMP for both 1-D and 2-D signal reconstruction. For 1-D signal reconstruction, probability damping brings most of the improvement. For 2-D signal reconstruction, weighting technique makes the major contribution. In summary, WDAMP outperforms conventional AMP.

This paper considers an OFDM wiretap channel with a legitimate transmitter (Alice), multiple legitimate receivers (Bobs), and an eavesdropper (Eve). Alice simultaneously transmits confidential message to each individual Bob. The timedomain Artificial noise (AN) is firstly employed to the wiretap OFDM channel with multiple Bobs. Under the proposed AN approach, a nonconvex sum secrecy rate maximization problem is formulated to jointly optimize subcarrier allocation, power allocation and AN design. To solve this tough problem, the optimal subcarrier allocation is found at first, and then a low-complexity Lagrange dual method is developed to jointly optimize power allocation and AN design. Finally, numerical results demonstrate the effectiveness of the proposed algorithms, including power allocation gain, AN gain and multiuser gain.

The current wireless communication network is a content-careless network, in which every request needs a new transmission, even those requests imply the same content. However, the Long-Tail distribution of users' interests caused by the converging behavior, determines that the redundant traffic, which is the re-transmission bearing same content, is rather enormous. Therefore the content-careless scheme of network transmission introduces large energy waste. In our previous work, we put forward a novel transmission scheme CASoRT to mitigate such energy waste by broadcasting those hot contents. After the contents are broadcast, the terminals in coverage could cache those contents in local memory and load those contents when request. Thus, the massive redundant transmission of the very content is relieved by one broadcast transmission. In order to exploit the advantage of broadcast, the proper recommender scheme, deciding which contents should be broadcast, needs to be optimized. In this paper, we present certain perspective in analyzing the log of campus network in Tsinghua University. It shows that utilizing users converging character could improve the efficiency of CASoRT with analysis. Finally, location based content recommendation scheme is proposed, verified by simulation.

Spatial Modulation is a newly developed concept for multi-antenna systems, which could greatly reduce the signal processing complexity and hardware implementation burden faced by these systems today. To improve the spectral efficiency of spatial modulation system, a novel precoding scheme for downlink multi-user system is proposed in this paper. The precoding scheme not only cancels the inter-user interference, but also preserves the information embedded both in constellation symbols as well as in transmit antenna indexes, decomposing the system into independent single-user spatial modulation systems. Simulation results show that with a high transmission rate, the proposed scheme offers a smaller bit error rate than multi-user Zero Forcing precoding in practical SNR region. With the same base station antenna number and single-antenna user number, it also outperforms Zero Forcing precoding in terms of achievable sum rate. Furthermore, systems using our scheme could achieve a multi-user gain over single-user spatial modulation system.

Coexistence research for LTE systems is indispensable to ensure that the time division duplex (TDD) Long Term evolution (LTE) system can coexist with the frequency division duplex (FDD) LTE system operating at the adjacent frequency band within the same geographical area. Previous studies on this topic only focus on the throughput loss of the victim system from the data channel viewpoint. In this paper, the performance of control channels (CCHs) in the typical coexistence scenario is investigated, since the performance of communication systems is largely dependent on the quality of CCHs. The CCHs' interferences are analyzed in detail, including the coexistence issue for CCHs, Co-Channel Interference (CCI) analysis, and Adjacent Channel Interference (ACI) on CCHs. The simulation results indicate that the ACI generated by the Base Station (BS) of collocated LTE system degrades the performance of the uplink (UL) CCHs of the victim LTE system significantly.

In this paper, a two-way relay channel is considered, where two sources transmit information to each other with the help of a half-duplex decode-and-forward (DF) relay. We investigate the energy efficiency (EE) for the DF two-way relay transmission (TWRT). The EE expression is derived first and the properties of the EE are then analyzed. An novel algorithm is proposed to find the maximal EE under the relay power constraint for the DF-TWRT. Simulation results confirm the theoretical findings of the EE for the DF-TWRT.

In recent years, energy consumption of information and communication industry have received more and more attention. But the energy efficient optimization problem of interference-limited system is difficult to solve because it is a non-convex problem. In order to deal with this problem, two sub-optimal algorithms, based on dual theory and differ-concave theory respectively, are proposed in this paper. Under different signal to interference and noise ratio (SINR), there must have one of these algorithms can achieve the energy efficient upper bounder of interference-limited system. Besides the energy efficient performance, the proposed algorithms also have low complexity. the simulation results show that the proposed algorithms can get great convergence property by choosing initial value carefully.

Cognitive-radio-networks with multiple input multiple output is an effective method to improve spectrum efficiency. Linear pre-coders is a crucial technology to realize this goal. However, most of existing algorithm developed based on the Gaussian input assumption. This assumption limited the application of linear precoding and caused great performance loss. In this paper, for such a problem, a linear pre-coders algorithm for maximizing the secondary users spectrum efficiency is designed. Different from previous spectrum efficient algorithm which is developed under the Gaussian input assumption, the proposed algorithm can work under any input assumption by inheriting the advantage of mercury water filling algorithm (MWF) and singular value decomposition (SVD). Numerical results show that the proposed algorithm exhibits a large gain over existing algorithms when we take a practical modulation type.

SUMMARY Cognitive radio (CR) can significantly alleviate the network pressure caused by the rapid development of wireless communications through allowing secondary users (SUs) to obtain spectrum resource from primary users (PUs). One key issue of CR technology is spectrum sharing, that is, how spectrum should be allocated between SUs without causing interference to PUs. In this paper, we propose abilateral bargainingmechanism to achieve this goal between two SUs. The general network scenario with multiple SUs can be decomposed into multiple pairs of bilateral bargaining studied in this paper. The SUs have to reach a mutual satisfactory agreement on the partition of spectrum by making alternating offers to each other. We model such bargaining process as dynamic finite/infinite horizon multistage game with observed actions and fully characterize the corresponding subgame perfect equilibria. Moreover, theoretical analysis and numerical results indicate that our proposed scheme can effectively allocate spectrum resource between SUs. Copyright © 2012 John Wiley & Sons, Ltd.

In this study, the authors mainly study the degrees of freedom (DoFs) of M × N user single input multiple output (SIMO) (or multiple input single output (MISO)) X channels, in which the channel coefficients are drawn from a continuous distribution and data‐sharing among users are unavailable. First, the authors establish an outer bound of DoFs for multiple‐in multiple‐out (MIMO) X channel, which is tighter than those in previous work. For SIMO X channel with R antennas at each user, the authors prove that the DoFs is [ MNR /( M + NR − R )], which is achieved by symbol extension and interference alignment. As the transmitters and receivers are interchangeable in the network considered, the authors obtain corresponding results for MISO X channel. Finally, the authors generalise our result to MIMO X channel with R antennas at each user, and show that its DoFs is [ MNR /( M + N − 1)].

Cooperative spectrum sharing can effectively improve the spectrum usage by allowing secondary users (SUs) to dynamically and opportunistically share the licensed bands with primary users (PUs). In return, an SU will relay a PU's traffic to improve the PU's effective data rate. In this paper, we study how one PU and one SU achieve an efficient spectrum sharing through dynamic noncooperative bargaining. The key challenge is that the PU does not have complete information of the SU's energy cost. We model the dynamic bargaining with incomplete information as a dynamic Bayesian game, and investigate the equilibria under both single-slot and multi-slot bargaining models. Theoretical analysis and numerical results indicate that our proposed scheme can lead to a win-win situation, where both the PU and the SU obtain data rate improvements via the bargaining-based CSS mechanism. Furthermore, the SU can take advantage of the incomplete information to improve its bargaining power (also called reputation effect), and thus gain a higher data rate.

Optimal power allocation for orthogonal frequency division multiplexing (OFDM) wiretap channels with Gaussian channel inputs has already been studied in some previous works from an information theoretical viewpoint. However, these results are not sufficient for practical system designs. One reason is that discrete channel inputs, such as quadrature amplitude modulation (QAM) signals, instead of Gaussian channel inputs, are deployed in current practical wireless systems to maintain moderate peak transmission power and receiver complexity. In this paper, we investigate the power allocation and artificial noise design for OFDM wiretap channels with discrete channel inputs. We first prove that the secrecy rate function for discrete channel inputs is nonconcave with respect to the transmission power. To resolve the corresponding nonconvex secrecy rate maximization problem, we develop a low-complexity power allocation algorithm, which yields a duality gap diminishing in the order of O(1/√N), where N is the number of subcarriers of OFDM. We then show that independent frequency-domain artificial noise cannot improve the secrecy rate of single-antenna wiretap channels. Towards this end, we propose a novel time-domain artificial noise design which exploits temporal degrees of freedom provided by the cyclic prefix of OFDM systems to jam the eavesdropper and boost the secrecy rate even with a single antenna at the transmitter. Numerical results are provided to illustrate the performance of the proposed design schemes.

This paper investigates the distributed power allocation problem for coordinated multipoint (CoMP) transmissions in distributed antenna systems (DAS). Traditional duality-based optimization techniques cannot be directly applied to this problem, because the non-strict concavity of the CoMP transmission's achievable rate with respect to the transmission power induces that the local power allocation subproblems have non-unique optimum solutions. We propose a distributed power allocation algorithm to resolve this non-strict concavity difficulty. This algorithm only requires local information exchange among neighboring base stations serving the same user, and is thus flexible with respect to network size and topology. The step-size parameters of this algorithm are determined by only local user access relationship (i.e., the number of users served by each antenna), but do not rely on channel coefficients. Therefore, the convergence speed of this algorithm is quite robust to channel fading. We rigorously prove that this algorithm converges to an optimum solution of the power allocation problem. Simulation results are presented to demonstrate the effectiveness of the proposed power allocation algorithm.

In this paper, the problem of joint power allocation (PA) for the downlink of a multi-cell distributed antenna system (DAS) is addressed. Motivated by practical applications, we focus on a reasonable scenario that only the large-scale channel state information at the transmitter (CSIT) is available. Based on the observation that the capacity-achieving input covariance for each cell is diagonal and that PA optimization is enough to achieve the maximum ergodic sum capacity, we formulate a joint PA optimization problem to maximize the ergodic sum capacity of the system with a total transmit power constraint for each cell. A rather precise closed-form approximation of the ergodic sum capacity is then introduced and taken as the objective function instead so that the original joint PA optimization problem can be simplified. Finally, we propose an iterative PA scheme based on the simplified joint PA optimization problem, in which Signomial Programming (SP) is used. Monte Carlo simulations show that the proposed scheme converges quickly and can offer nearly optimal system ergodic sum capacity. Thus, we refer the proposed PA scheme as a suboptimal one. Moreover, from the simulations we can see that a significant performance gain can be achieved by multi-cell joint PA in DAS with only large-scale CSIT.

Relative to the Triple Modular Redundancy (TMR) scheme, the arithmetic residue codes based fault-tolerant DSP design consumes much less resources. However, the price for the low resource consumption is the fault missing problem. The basic tradeoff is that, smaller modulus used for the fault checking consumes fewer resources, but the fault missing rate is higher. The relationship between the value of modulus and the fault missing rate is analyzed theoretically in this paper for fault-tolerant FIR filter design, and the results are verified by FPGA implemented fault injections.

In this paper we present some channel measurement results of distributed multiple-input multiple-output (D-MIMO) systems inside a MD-82 aircraft. Channel capacity and spatial correlation are analyzed from the measured channel matrix. Capacity results of 7 different systems (six D-MIMO systems and a SISO system) are discussed. It is found that D-MIMO systems yield significant capacity gains as compared to SISO system. Spatial correlations among transmitter (Tx) antennas distributed above the cabin aisle are statistically analyzed from the measured data. Result shows that, when receiver (Rx) antenna array is placed in the front or back of the cabin, some Tx antenna pairs are highly correlative (correlation coefficients are higher than 0.8). The effect of Tx antenna selection on capacity characteristic of in-cabin D-MIMO system is also studied. It is found that Tx antenna selection can further improve channel capacity and the optimum selected Tx antennas are usually the ones near to the Rx array.

Since the standardization of Long Term Evolution - Advanced (LTE-A) is currently carried through in 3rd Generation Partnership Project (3GPP), it is of great importance to ensure the coexistence between LTE-A system and other mobile systems. This paper is aiming at presenting the performance loss of 3G/B3G TDD systems (TD-SCDMA, TD-HSDPA and TD-LTE) interfered by LTE-A system. The detailed interference models are analyzed theoretically. Afterwards, three representative interference scenarios are simulated by adopting Monte Carlo method and discussed from the following respects: inter-site distances (ISD), offsets between two systems, carrier frequency, frequency reuse schemes, uplink power control mechanism and system bandwidth of TD-LTE. In the end, a few suggestions concluded through simulation results are proposed to better realize the co-deployment of LTE-A and 3G/B3G TDD systems.

In this paper, we discuss a fairness energy algorithm for the M2M renewable network. The algorithm mainly contains the flow control and transmission strategy and has low computational complexity. The aim is to reach an asymptotically optimal average network performance while keeping the fairness among nodes.

In this paper, we address the problem of coordinated user scheduling for the downlink of a multi-cell distributed antenna system (DAS). With the practical assumption that only large-scale channel state information (CSI) is known at the transmitter, a low-complexity greedy scheduling scheme is proposed. In order to provide fairness among users, the proposed scheme adopts round-robin scheduling within each cell and optimizes the scheduling order for each cell to maximize the minimum ergodic capacity of the users. For each user, the selection transmission scheme (just the distributed antenna element (DAE) with the largest channel gain to the user is selected for transmission) is implemented and each selected DAE transmits with equal power. Simulation results demonstrate that the proposed greedy scheme promises much better performance than that without inter-cell coordination and its performance is quite close to the optimal one. Moreover, by simulations we find that the proposed scheme achieves nearly the same system ergodic sum capacity with the one targeted to maximize the system ergodic sum capacity.

Cooperative spectrum sharing can effectively improve spectrum usage by allowing secondary users (SUs) to dynamically share the licensed bands with primary users (PUs). Meanwhile, an SU can relay a PU's traffic to improve the PU's effective data rate. In this paper, we consider a sequential spectrum bargaining process to achieve cooperative spectrum sharing between one PU and one SU over multiple time slots. The SU may be a Low type or a High type, depending on its energy cost. Such information is private to the SU and is unknown to the PU. We model such a dynamic bargaining with incomplete information as a dynamic Bayesian game, and characterize several types of equilibria under different system parameters. In particular, we show that a Low type SU may maximize its total utility by utilizing the reputation effect, i.e., rejects profitable offers initially in order to create the reputation of a High type SU.

In this paper we propose a novel algorithm to predict the performance of interleaver division multiple access (IDMA) systems, which is called mutual information evolution algorithm (MIEA). The proposed MIEA is a semi-analytical technique, which is based on but a little different from the traditional extrinsic information transfer (EXIT) chart especially when used for the successive interference cancellation (SIC) structure in IDMA systems. Based on MIEA, not only the convergence behavior of iteration structures in IDMA systems can be analyzed, but also the trade-off between code-rate (CR) and spreading-factor (SF) can be obtained. Moreover, the MIEA can be used to search the optimal codes in IDMA. Simulation results are also presented to confirm our analysis.

In this note, we point out a few problems with the proof for Theorem 1 and Theorem 2 in the above-mentioned paper and give a correct version for the incorrect parts.

Interference cancellation (IC) is an effective and easy implemented technology in the multi-user system. Previous studies demonstrate the principles of IC and IC process which show a great improvement in the system capacity with IC. However, no research has focused on the IC system's capacity domain by giving an accurate formula. This article carries on the theoretical analysis of CDMA reverse link capacity with IC, presents the expressions as well as its optimal answer for synchronous frame and brings forward the formula as well as its suboptimal solution for asynchronous frame. Numerical result reveals that the commercial EV-DO reverse link capacity with IC will increase by at least 135% compared with the one without IC. Finally, the stability of the IC system is explored.

Cooperative energy spectrum sensing has been proved effective to detect the spectrum holes in Cognitive Radio (CR). However, its performance may suffer from the noise uncertainty, which is portrayed by the SNR wall in some literatures. In this paper we analyze the spectrum sensing performance under noise uncertainty and propose a new approach to obtain the SNR wall. In addition, a suboptimal liner cooperative sensing algorithm with wavelet denoising is proposed to reduce the impact of noise uncertainty. Analysis and numerical results show that cooperative sensing and wavelet denoising can significantly improve the sensing performance under noise uncertainty condition.

Cooperative energy spectrum sensing has been proved effective to detect the spectrum holes in Cognitive Radio (CR). However, few studies make mention of wavelet transform based signal processing before energy detection. In this paper, a novel cooperative energy spectrum sensing algorithm with 1-D or 2-D wavelet denoising is proposed. The 1-D wavelet denoising is performed at each sensing node, while the 2-D wavelet denoising is implemented at the sensing station. Simulation results show that the spectrum sensing performance is improved significantly by the proposed cooperative spectrum sensing algorithm with wavelet denoising as opposed to the conventional method.

To ensure Evolved-Universal Terrestrial Radio Access Network (E-UTRA) or Long Term Evolution (LTE) can coexist with other mobile systems operating in the same geographical area, coexistence studies involving E-UTRA are ongoing in the 3rd Generation Partnership Project (3GPP). Related work is also on the way in China Communications Standards Association (CCSA) which may influence the allocation of frequency bands. In this paper, coexistence issues between E-UTRA and Universal Terrestrial Radio Access Network (UTRA) deployed in adjacent frequency bands are investigated. Two classical approaches are used to evaluate the performance degradation of both systems caused by inter-system interference. One is theoretical analysis and the other is system level simulation. The deterministic calculation is carried out in detail for base station (BS) to BS interference scenario, while the static Monte-Carlo simulation is adopted to analyze almost all the interference scenarios. System level evaluation methodology and assumptions are provided, and simulation results for a number of typical scenarios are discussed. The results show that E-UTRA has the ability to resist interference to some extent, but it brings severe interference to UTRA, and the interference between base stations is more severe than other scenarios. It is also found that the offset of E-UTRA system sites, different frequency bandwidths and power control schemes have various impacts on UTRA performance, so they should be carefully considered during E-UTRA deployment to ensure the coexistence with UTRA.

In this paper, a novel analytical model structure for wideband multiple-input multiple-output (MIMO) channel is presented. It is based on the power coupling between direction of departure (DoD), direction of arrival (DoA) and delay domain. As its realizations, firstly the singular value decomposition (SVD) based model is introduced and the virtual presentation model is extended to the wideband situation. Then a hybrid model is given on basis of the power coupling between the transmit eigenmodes, receive eigenmodes and frequency steering vectors. The hybrid model can provide the tradeoff between the complexity and accuracy. At last, the novel coupling-based model structure is summarized. With a 3.52 GHz wideband MIMO sounder, measurements are carried out in different indoor scenarios. Monte Carlo simulations are used to generate the channel realizations according to these proposed wideband models. Good agreements are achieved between the discussed models and measured data.

Block diagonalization (BD) is a low-complexity linear preceding scheme for multiuser MIMO (MU-MIMO) downlink, which can completely eliminate multi-user interference with perfect channel state information (CSI) at the transmitter. Under the assumption of block fading channels, BD with fixed amount of feedback is interference-limited. In this paper, we first introduce a low-complexity CSI feedback scheme, by exploiting the temporal correlation of practical channels, to improve the efficiency of feedback. Then, a modified BD algorithm is proposed to further utilize the channel correlation in time domain. Combined with the CSI feedback scheme, the modified BD algorithm handles the interference-limiting problem in a wide range of SNR with a fixed, small number of feedback bits.

In this paper, the uplink of a multi-user distributed antenna system (DAS) with antenna elements deployed on a circle is investigated. We address the problem of calculating the sum-rate capacity with per-user power constraints. Based on system scale-up, we derive a good approximation of the sum-rate capacity by adopting random matrix theory. We also propose an iterative method to calculate the unknown parameters in the approximation. The approximation is illustrated to be quite accurate and the iterative method is verified to be quite efficient by Monte Carlo simulations.

In this paper, the downlink performance of distributed antenna systems (DAS) with random antenna layout is investigated. We consider the composite channel including large-scale fading and small-scale fading. When the large-scale channel state information, which usually varies slowly and is easy to be obtained, is available at the transmitter, the problem of power allocation among distributed antennas with the target of downlink capacity maximization is formulated. Based on system scale-up, we derive a precise approximation of the downlink ergodic capacity by adopting random matrix theory. We also propose an iterative method to calculate the unknown parameter in the approximation. Moreover, the approximation is proved to be concave on the transmit powers of the distributed antennas. Consequently, a simple sub-optimal power allocation scheme is proposed, with which the system capacity is illustrated to be quite close to the optimal one obtained by numerical optimizations.

Multicell processing (MCP) techniques have attracted considerable research attention since they can effectively mitigate other-cell interference (OCI). However, the potential gain of MCP comes with several practical challenges including huge overhead and stringent synchronization requirements. In this paper, we propose cooperative opportunistic scheduling to coordinate OCI for downlink transmission in multiple antenna cellular networks, which incurs less overhead and relaxes synchronization requirements. As a baseline for comparison, we study the average throughput with noncooperative opportunistic scheduling and derive the throughput expression in closed form. We show that the scaling law of average throughput with noncooperative opportunistic scheduling follows the log log K form, where K is the number of users per cell. Furthermore, with the assumption that adjacent cells can exchange channel state information, we propose a cooperative opportunistic scheduler. Using extreme value theory, we obtain concise expression for the average throughput with the cooperative opportunistic scheduler, which is proven to scale like log K. Our analysis are verified by simulation results.

The combination of relay and Multiple-Input Multiple-Output (MIMO) techniques can significantly benefit the signal transmission in cellular networks. In this work, we propose a novel relaying scheme for the relay assisted MIMO broadcast channel including user classification and preceding. The users are firstly classified as Direct Link (DL) users and Relay Link (RL) users according to their channel conditions. After classification, both DL and RL users may coexist in the system, and Zero-Forcing (ZF) preceding is employed at both the BS and the relay for interference cancellation. Analysis and simulation results show that the proposed relaying scheme can effectively combat the large scale fading of the channels and provide significant performance gain compared with the conventional MIMO relaying schemes without user classification.

In this paper, the downlink performance of a distributed antenna system (DAS) with random antenna layout is investigated. We address the problem of characterizing the downlink capacity with the generalized assumptions: (al) per distributed antenna power constraint, (a2) generalized mobile terminals equipped with multiple antennas, (a3) a multi-cell environment. Based on system scale-up, we derive a good approximation of the ergodic downlink capacity by adopting random matrix theory. We also propose an iterative method to calculate the unknown parameter in the approximation. The approximation is illustrated to be quite accurate and the iterative method is verified to be quite efficient by Monte Carlo simulations.

In this paper, we propose a limited-feedback preceding scheme, successive and dynamic per-user rate control (SD- PURC), in the multiuser multiple-input multiple-output (MIMO) downlink systems. This scheme is characterized by the successive process of scheduling and the dynamic adjustment of correlation parameters with regard to a set of non-orthogonal precoding vectors. Simulation results indicate that relative to the existing precoding scheme, per-user unitary rate control (PU2RC), the successive and dynamic mechanism in the proposed scheme can greatly improve the system sum-rate performance with less feedback amount.

This paper addresses the problem of joint transceiver design for Tomlinson-Harashima Preceding (THP) in the multiuser multiple-input-multiple-output (MIMO) downlink. Different from previous work, we perform stream-wise (both inter-user and intra-user) interference pre-cancelation at the transmitter. A minimum total mean square error (MT-MSE) criterion is used to formulate our optimization problem. By some convex analysis of the problem, we obtain the necessary conditions for the optimal solution. Then an iterative algorithm is proposed to handle this problem and its convergence is proved. Simulation results are given to verify the efficacy of our proposed scheme and to show its superiority over existing THP-relevant schemes.

This paper investigates optimal transmission of space-time block codes (STBCs) in distributed multiple-input multiple-output (D-MIMO) Rayleigh fading channels. The optimal diversity performance is achieved through transmit power allocation implemented at the receiver based on transmit and receive correlations to minimize the average symbol error rate (SER). Evaluation of SER performance of uncoded STBCs over a generalized distributed antenna (DA) topology is first presented, with exact analytical SER expressions derived for MQAM and MPSK symbols. SER upper bounds are also derived, based on which two criteria for complexity reduced antenna subset selection with sub-optimal power allocation are further proposed, whose performance approaches optimal over correlated D-MIMO channels. Moreover, a novel simplified but close SER approximation scheme is devised to significantly facilitate optimal SER calculation. We continue to thoroughly analyze how the optimal diversity is affected by large scale fading, targeted data rate, antenna correlations and transmit power. Finally, we develop a surprisingly close and useful analogy between open loop STBCs in co-located MIMO and optimal STBCs in D-MIMO with minimum feedback (i.e., n bits for n DAs in Criterion 2 with power allocation scheme 2 which equally allocates power to the selected DAs). Extensive simulation results have been presented to demonstrate the effectiveness of our analysis.

In this paper, the investigation of Tomlinson-Harashima precoding (THP) in downlink multiuser multiple- input multiple-output (MIMO) systems with imperfect channel state information (CSI) is carried out, including two basic structures according to the positions of the diagonal weighted filter: decentralized at the receivers or centralized at the transmitter, which are named as dTHP or cTHP, respectively. The interference power in layers caused by imperfect CSI is first derived, then the comparison between these two THP structures and the linear zero-forcing (ZF) precoding is performed, in terms of interference power and system capacity. Moreover, the independence of the interference powers among layers is presented. Simulation results indicate that with imperfect CSI, THP leads to smaller interference power than linear-ZF, and dTHP leads to larger system capacity than cTHP and linear-ZF.

In this paper, we investigate the optimal power allocation strategy that aims at maximizing the capacity in OFDM- based cognitive radio systems. We show that the traditional water-filling algorithm applied in general OFDM systems needs to be modified due to the per subchannel power constraints in such systems. An iterative partitioned water-filling algorithm is proposed and proved to be optimal based on the convex optimization theory.

In orthogonal frequency-division multiplex access (OFDMA) systems, including uplink and downlink, the carrier- frequency offset (CFO) between the multiple transceivers introduces inter-carrier interference (ICI). In this paper, we first develop the uplink-downlink duality of ICI cancellation in OFDMA systems with CFO, then propose a uniform iterative ICI cancellation scheme that can be applied to both uplink and downlink. In uplink, this scheme acts as the detection at the receiver, while in downlink, it acts as the preceding at the transmitter. Moreover, by the studies of the convergence behavior of the iterations, a sufficient condition for the convergence is given, and it is proved that this iterative scheme is equivalent to the zero-forcing (ZF) scheme, but with much lower complexity. The simulation results indicate that due to the uplink-downlink duality, this iterative scheme can effectively suppress the ICI due to CFO in both uplink and downlink.

In this paper, we investigate the uplink of a power- controlled multi-user distributed antenna system (DAS) with antennas deployed on a circle. Applying results from random matrix theory, we prove that the per-user sum rate and the total transmit power both converge as user number and antenna number go to infinity with a constant ratio. The relationship between the asymptotic per-user sum rate and the asymptotic total transmit power is established. We then deal with a typical path loss exponent of 4, present the rate-power relationship in a closed form and find the optimal circle radius for antenna deployment. Simulation results are also provided to demonstrate the validity of our analysis.

Distributed wireless communication system (DWCS) has been considered as a promising architecture for future wireless access networks. In this paper, we develop an adaptive transmit-receive mode selection scheme for a multi-user system with this architecture. In the proposed scheme, large-scale fading information between users and antennas is employed to decide the most appropriate mode from three available modes named independent processing mode, joint processing mode and time division mode. Selection criterion for a system with two single-antenna users and two distributed antennas is discussed in detail. Numerical results indicate that the proposed scheme achieves high capacity with relatively low complexity.

In cognitive radio (CR) systems, secondary users (SUs) have to detect the channel periodically during their data transmission to decide whether the channel is idle in order to avoid unacceptable interferences to primary users (PUs). The duration of the detection process in a cycle affects the channel efficiency of the SU. Also, the detection time needs to be adaptively adjusted due to path loss variations caused by movements of PUs and SUs. In this paper, we explore the issue on the detection time selection that aims at improving the channel efficiency. We formulate this issue as an optimization problem, but it is extremely difficult to get the explicit solution. A numerical optimization algorithm is proposed to obtain the numerical solution to the problem. Numerical results show that the highest channel efficiency can be achieved by the optimization of the detection time.

Connected dominating set (CBS) has been proposed as virtual backbone or spine of wireless ad hoc networks. Most literatures take the same assumption that the ad hoc network is distributed in a 2-dimensional plane. In this paper, the characters of CBS structure are deduced to 3-dimensional space, and a distributed approximation algorithm is analyzed for ad hoc network, whose performance ratio is proved to be 16 at most, in the case of 3-dimensions.

A low-complexity Kalman-filter-based channel estimation method for orthogonal frequency-division multiplexing systems is proposed. This method belongs to the pilot-symbol-aided parametric channel estimation method in which the channel responses are characterised as a collection of sparse propagation paths. Because of the slow variation of the signal subspace in the channel samples' correlation matrix, the estimation of channel parameters is translated into an unconstrained minimisation problem. Then, in order to solve this optimisation problem, a subspace tracking by Kalman filter is carried out, which is characterised in that the state equation and the measurement equation are constructed upon the constant signal subspace. Further, this Kalman-filter-based method is extended to the multi-antenna scenarios efficiently. Simulation results show that the proposal can effectively track the time variations in both the block fading channels and the Doppler frequency spread channels.

This letter investigates optimal transmission of orthogonal space-time block codes (OSTBCs) over distributed antennas (DAs) in non-ergodic flat Rayleigh fading channels with transmit antenna correlations. A generalized DA topology is considered, where the DAs are grouped into some geographically dispersed ports within each of which the DAs are co-located. Assuming equal power allocation within each port, the outage probability is derived. We find that minimizing the outage probability only requires the feedback of the eigenvalues of the transmit correlation matrix at the transmitter. Since it is computationally intensive to minimize the outage probability, an antenna subset selection with suboptimal power allocation scheme is proposed, whose effectiveness has been demonstrated by numerical results

In this paper, a group of low-complexity subspace tracking based pilot-aided channel estimation methods for orthogonal frequency-division multiplexing (OFDM) systems is studied. These methods are based on a parametric channel model where the channel response is characterized as a collection of sparse propagation paths. Considering the slow variations of the channel correlation matrix's signal subspace, we first translate the estimation of channel parameters into an unconstrained minimization problem. Then, to solve this minimization problem, a novel Kalman-filter based subspace tracking method is proposed, which employs the constant signal subspace to construct state equation and measurement equation. In contrast, other two adaptive filters, LMS and RLS, are applied and evaluated. These three methods constitute a group of low-complexity subsapce tracking schemes. It is shown that the proposed Kalman filter method is able to effectively track the time-varying channels, and outperforms LMS and RLS methods with large Doppler frequency spread.

Turbo codes employ iterative decoding through the exchange of extrinsic information (EI) on systematic bits between two parallel concatenated recursive systematic convolutional (RSC) codes. The EI on parity bits can not be utilized during iterative decoding. In this paper, we propose a new type of iterative decoding scheme mapping parity bits of turbo codes to a multi-dimensional (MD) QPSK, which makes it possible to utilize the EI on parity bits by iterative demapping. We use extrinsic information transfer (EXIT) chart to predict the system's convergence behavior and to help search good RSC codes and MD QPSK schemes. An analytical upper bound is also given to show the system's asymptotic performance in medium to high E/sub b//N/sub 0/ region. We introduce two special schemes and do simulations on them. Particularly, the scheme with turbo code consisting of two 4-state (7, 6) codes and an eight dimensional QPSK outperforms Berrou turbo code with two 16-state RSC codes in water fall region and has similar error floor.

In this paper, we address the problem of designing jointly the linear transmitter and receiver for the downlink of multiuser MIMO system, using minimum the total mean square error criterion (T-MMSE), subject to a total transmit power constraint. We show that the optimum transmitter and receiver under such design criterion could be realized through a joint iterative algorithm. The convergence of the proposed algorithm is proved. The analysis and simulation results have both shown the feasibility of this new method.

This paper studies downlink transmits antenna selection with power and rate allocation in generalized distributed wireless communication systems (G-DWCS). Based on the large-scale fading statistics (path loss and shadow fading) at the transmitter, antenna selection criteria have been proposed for combined space time block code (STBC) and Vertical Bell-Labs Layered Space Time (V-BLAST) structure, where each layer of V-BLAST is composed of co-located multiple antennas for independent STBC transmission. The sub-optimal antenna set, sub-optimal power and rate allocation are determined to minimize an upper bound on the symbol error rate (SER). At the receiver a fixed detection order is followed which is obtained meanwhile in the antenna selection process at the transmitter. It's verified by Monte Carlo simulation that our proposed antenna selection criteria can judiciously select the optimal antenna set and allocate proper power and rate, and are very suitable for G-DWCS system.

Direct-sequence code-division multiple access (DS-CDMA) is a popular wireless technology. In DS-CDMA communications, all of the users' signals overlap in time and frequency and cause mutual interference. Serial interference cancellation (SIC) multiuser detection is a very promising low complexity approach to handle this problem. In conventional single timeslot based SIC scheme, SIC is performed first, then followed by deinterleaving and Viterbi decoding which use the outputs of the last stage of the SIC as the input. In this paper, a novel multiple timeslots based SIC multiuser detection scheme for coded synchronous DS-CDMA is proposed. The new detector performs joint multiple timeslots successive interference cancellation (JMT-SIC) and Viterbi decoding (VD) in each step of the interference cancellation. Simulation results within the framework of the third generation wireless communication standard TD-SCDMA has shown that the BER performance of the proposed scheme is much better than the conventional one.

In this paper, we investigate the capacity of continuously time-varying multiple-input multiple-output (MIMO) systems in frequency-flat Rayleigh fading environment with perfect interleaving. By introducing the Gauss-Markov model to describe the channel variation and employing minimum mean square error (MMSE) channel estimation based on the pilots, we derive very tight lower and upper bounds of the ergodic capacity in closed-form. We also derive the optimal power allocation between the pilot and data vectors, which maximize the lower bound of the ergodic capacity. Interestingly, the optimal allocation is independent of the channel variation parameter and can be easily computed (no feedback is required). The optimal training interval can be obtained via numerical optimization. Finally, two different transmit schemes are compared via simulation. It is shown that, in fast fading or high SNR environments, the scheme with optimal power allocation almost has the same performance as the scheme with equal power allocation. However, in slowly fading or low SNR environments, the former has much better performance than the latter.

Low-complexity tree search based exact maximum-likelihood (ML) detectors have gained attention for optimum signal detection in multiple-input multiple output (MIMO) wireless systems. In this paper, taking a fresher look at the closet lattice point search problem, we propose a new fast exact ML sphere decoder with ever-increasing radius (IR-SD). It is shown that IR-SD visits minimum number of tree nodes and is more computationally efficient than existing sphere decoders. IR-SD is also faster and requires less storage than ML stack detector. An upper-bound of expected computation and storage complexity of IR-SD independent of tree radius is derived. Numerical results validate that IR-SD greatly speeds up the ML detection than other sphere detectors while requiring less storage than ML stack algorithm. A factor-of-2.5 speed-up is observed over the depth-first Schnorr-Euchner sphere decoders when utilizing IR-SD in 16-QAM 10/spl times/10 complex MIMO system.

In the multiinput multioutput (MIMO) wireless communication system, especially in the V-BLAST, the received signal vectors detection is the crucial part that impacts the system performance. This paper introduces a new V-BLAST detector that can gain more diversity gain. This detector utilizes the successive interference canceling (SIC) and parallel interference canceling (PIC), during the iteration of SIC and PIC, turbo code is used to guarantee the reliability of PIC. Compared with other detection algorithm, this new iterative detector can enhance the receive diversity. This paper simulates the algorithm with OFDM modulation under multipath Rayleigh MIMO channel. From the simulation results, the system performance can be improved and the complexity of this iterative detector is very low.

Spatial fading correlation severely impairs the performance of an antenna array system that relies on space diversity capability. In this paper, we first reviewed the general closed-form expression for the fading correlation function which could be applied to various array geometries and energy distributions of angle-of-arrival (AOA) in a mobile radio environment. Then, we applied them in studying the fading correlation under the case of multi-cluster arriving, and analyzed the correlation matrix for different antenna array structure.

The stable adaptive routing protocol (SAR) is a novel on-demand stable adaptive routing protocol for ad hoc network proposed last year, which considers joint route hop counts, node stability and route traffic load balance as the route selection criteria in routes searching and maintain. This paper describes the performance evaluation of SAR protocol by a practical ad hoc network test-bed under typical indoor and outdoor environments. And compared to AODV routing protocol, SAR has better performance on system cost, successfully delivery ratio and average delay jitter, as shown in the measurement results.

In this paper, we propose a new MAC protocol for ad-hoc networks that uses multiple channels and a dynamic channel selection scheme. The proposed protocol, DCC-MAC (dual control channel based MAC), deploys two control channels (CH/sub R/C/ and CH/sub ACK/ and N data channels, where N is independent of the number of nodes in the network. Through RTS/CTS dialogues on CH/sub R/C/ senders and receivers negotiate the most robust channel for data transmission with maximum-CIR selection criterion. ACK transmission on CH/sub ACK/ contributes to the unidirectional transmission on data channels and therefore the decrease of the co-channel reuse distance. Performance evaluation has been carried out and the simulation results demonstrate the effectiveness of the proposed protocol.

This paper presents frequency-domain equalization (FDE) using iterative channel estimation for high-speed transmission with cyclic-prefix multicarrier direct sequence spread spectrum CDMA (MC-DS-CDMA). Cyclic-prefix DS-CDMA simplifies many issues arising in receiver due to the high-speed transmission, such as delay-spread of the channel. It also reduces the complexity of the equalizer and enables the equalization in frequency domain. With pilot-aided channel estimation and OFDM-style cyclic prefixes, a frequency-domain MMSE equalizer achieves the suppression of multipath interference. Yet the accuracy of channel estimation restricts the performance of the equalizer. In order to acquire more accurate channel estimation, an iterative algorithm is presented in this paper. Simulation results show, with the employment of this algorithm, the performance of the frequency-domain equalizer has a significant improvement. Compared to the original RAKE receiver with severe interference, after 5 iterations, the SNR of despread signals is enhanced by about 13 dB. This higher SNR can satisfy the requirement of demodulator and decoder, and support the full usage of Walsh codes and high order modulation as well.

Routing algorithm has been the challenge in the wireless ad-hoc network for a long time because of the quick mutability of the network topology introduced by the mobility of nodes. AODV is appealing for ad hoc networks as an efficient on-demand routing protocol because of the low routing overhead and high performance. As an optimization for the current AODV, a novel stable adaptive enhancement for AODV routing protocol was proposed in this paper, which considers joint route hop count, node stability and route traffic load balance as the route selection criteria. Comparing with AODV protocol, the new algorithm has better performance as shown with the simulations results.

The paper presents the average bit error rate (BER) of a maximal ratio combining (MRC) two-dimensional (2D)-RAKE receiver in correlated frequency selective Nakagami fading environments in the presence of multiple co-channel interferences. A closed-form expression of the simple approximated probability density function for the signal-to-interference-plus-noise ratio (SINR) is derived for the receiver with multiple correlated antennas and multiple RAKE branches in arbitrary fading environments. The effects of spatial and temporal diversity order, angular spread, antenna spacing, average multi-path strength and fading severity on the performance of the MRC 2D-RAKE receivers are all illustrated.

The closed-form expressions of signal-to-interference-plus-noise ratio (SINR) and the outage probability are derived for a maximal ratio combining (MRC) two-dimensional (2D)-RAKE receiver with imperfect power control in a frequency-selective Nakagami fading channel. The impact of power control error (PCE) on the performance of the receiver is analyzed for various fading environments. Numerical results show that the performance of 2D-RAKE receivers degrades due to imperfect power control. But when PCE is not serious, increasing the number of antennae and temporal diversity order can compensate for the performance loss. The exact performance improvement due to space-time processing varies with PCE and the fading environment.

In this paper, output SINR performance of a smart antenna and two kinds of 2D-RAKE technology - combined and joint spatial-temporal 2D-RAKE - is compared in the same single cell DS-CDMA system. Average output SINR expressions are derived, with the parameters analyzed and performance compared.

The smart antenna and spatial diversity-combining receiver are two of the most important spatial signal processing technologies. This paper studies the radio propagation characteristics of the transmission path, spatio-temporal channel model and channel characteristics in different environments. On the basis of those analyses, the authors analyzed the operating principle of the smart antenna and spatial diversity-combining technology, and especially showed the differences between these two technologies in several aspects.

Research on next generation wireless communications integrated with current wireline networks is a potential issue considered worldwide. A novel wireless system, called distributed wireless communication system (DWCS), is proposed. Logically, it is divided into four layers. They are distributed antennas, a distributed fiber-optic transmission network, distributed processing network and a distributed core network. To support different radio access standards, the distributed processing network is realized with a software radio technique. Also, some new concepts, such virtual cell and virtual tunnel is proposed for DWCS. It is foreseen that the DWCS has three phases of development and how it conforms with the Internet is considered. Thus, the DWCS is a system that depends not only on wireless technologies, but also on Internet technologies. In terms of our description, the DWCS has the characteristics of an open distributed system with flexibility, scalability and expansibility.

Previously developed techniques for modulation classification have assumed that both the signal and noise power are known. However, the signal or noise power estimations require that modulation type is known. To solve the problem, this paper introduces a method for joint power estimation and modulation classification (JPEMC), whose key point is employing the relationships between the second- and higher moments of received signal and signal and noise power. Simulation results demonstrate the efficiency of modulation classification of JPEMC and indicate that the power estimation can be used by later demodulators.

A simplified and approximated probability density function (PDF) has been obtained for the signal-to-interference-plus-noise ratio (SINR) of the maximal ratio combining (MRC) 2D-RAKE receiver in a frequency-selective Nakagami multipath fading with arbitrary fading parameters, thus simplifying the analysis of bit error rate (BER) and outage probability in the presence of multi-path interferers. The numerical results indicate that the 2D-RAKE receiver could improve the system performance of WCDMA communication systems.

Adaptive channel estimation (ACE) and dedicated pilot power adjustment based on the fading-rate measurement is investigated for the pilot-aided direct-sequence (DS) code division multiple access (CDMA) system. A novel adaptive channel estimator is presented, which makes use of an optimum integral duration or selects the optimum finite-impulse response (FIR) filter coefficients based on the fading-rate measurement. Dynamic adjustment of the dedicated pilot power is further proposed for the purpose of increasing the system capacity, based on the fact that the power of the dedicated pilot channel (DPCH) can be reduced when the mobile station moves slowly. Theoretical analysis and computer simulation results show that significant performance improvement can be achieved by using the proposed adaptive channel estimator and the dynamic pilot power adjustment method.