From the Book:
“Clean code that works” is Ron Jeffries’ pithy phrase. The goal is clean code that works, and for a whole bunch of reasons:
Clean code that works is a predictable way to develop. You know when you are finished, without having to worry about a long bug trail.Clean code that works gives you a chance to learn all the lessons that the code has to teach you. If you only ever slap together the first thing you think of, you never have time to think of a second, better, thing. Clean code that works improves the lives of users of our software.Clean code that works lets your teammates count on you, and you on them.Writing clean code that works feels good.But how do you get to clean code that works? Many forces drive you away from clean code, and even code that works. Without taking too much counsel of our fears, here’s what we do—drive development with automated tests, a style of development called “Test-Driven Development” (TDD for short). 
In Test-Driven Development, you:
Write new code only if you first have a failing automated test.Eliminate duplication.

Two simple rules, but they generate complex individual and group behavior. Some of the technical implications are:You must design organically, with running code providing feedback between decisionsYou must write your own tests, since you can’t wait twenty times a day for someone else to write a testYour development environment must provide rapid response to small changesYour designs must consist of many highly cohesive, loosely coupled components, just to make testing easy

The two rules imply an order to the tasks ofprogramming:
1. Red—write a little test that doesn’t work, perhaps doesn’t even compile at first
2. Green—make the test work quickly, committing whatever sins necessary in the process
3. Refactor—eliminate all the duplication created in just getting the test to work


Red/green/refactor. The TDD’s mantra.

Assuming for the moment that such a style is possible, it might be possible to dramatically reduce the defect density of code and make the subject of work crystal clear to all involved. If so, writing only code demanded by failing tests also has social implications:
If the defect density can be reduced enough, QA can shift from reactive to pro-active workIf the number of nasty surprises can be reduced enough, project managers can estimate accurately enough to involve real customers in daily developmentIf the topics of technical conversations can be made clear enough, programmers can work in minute-by-minute collaboration instead of daily or weekly collaborationAgain, if the defect density can be reduced enough, we can have shippable software with new functionality every day, leading to new business relationships with customers


So, the concept is simple, but what’s my motivation? Why would a programmer take on the additional work of writing automated tests? Why would a programmer work in tiny little steps when their mind is capable of great soaring swoops of design? Courage.
Courage
Test-driven development is a way of managing fear during programming. I don’t mean fear in a bad way, pow widdle prwogwammew needs a pacifiew, but fear in the legitimate, this-is-a-hard-problem-and-I-can’t-see-the-end-from-the-beginning sense. If pain is nature’s way of saying “Stop!”, fear is nature’s way of saying “Be careful.” Being careful is good, but fear has a host of other effects:
Makes you tentativeMakes you want to communicate lessMakes you shy from feedbackMakes you grumpy

None of these effects are helpful when programming, especially when programming something hard. So, how can you face a difficult situation and:
Instead of being tentative, begin learning concretely as quickly as possible.Instead of clamming up, communicate more clearly.Instead of avoiding feedback, search out helpful, concrete feedback.(You’ll have to work on grumpiness on your own.) 

Imagine programming as turning a crank to pull a bucket of water from a well. When the bucket is small, a free-spinning crank is fine. When the bucket is big and full of water, you’re going to get tired before the bucket is all the way up. You need a ratchet mechanism to enable you to rest between bouts of cranking. The heavier the bucket, the closer the teeth need to be on the ratchet.

The tests in test-driven development are the teeth of the ratchet. Once you get one test working, you know it is working, now and forever. You are one step closer to having everything working than you were when the test was broken. Now get the next one working, and the next, and the next. By analogy, the tougher the programming problem, the less ground should be covered by each test.

Readers of Extreme Programming Explained will notice a difference in tone between XP and TDD. TDD isn’t an absolute like Extreme Programming. XP says, “Here are things you must be able to do to be prepared to evolve further.” TDD is a little fuzzier. TDD is an awareness of the gap between decision and feedback during programming, and techniques to control that gap. “What if I do a paper design for a week, then test-drive the code? Is that TDD?” Sure, it’s TDD. You were aware of the gap between decision and feedback and you controlled the gap deliberately.

That said, most people who learn TDD find their programming practice changed for good. “Test Infected” is the phrase Erich Gamma coined to describe this shift. You might find yourself writing more tests earlier, and working in smaller steps than you ever dreamed would be sensible. On the other hand, some programmers learn TDD and go back to their earlier practices, reserving TDD for special occasions when ordinary programming isn’t making progress.

There are certainly programming tasks that can’t be driven solely by tests (or at least, not yet). Security software and concurrency, for example, are two topics where TDD is not sufficient to mechanically demonstrate that the goals of the software have been met. Security relies on essentially defect-free code, true, but also on human judgement about the methods used to secure the software. Subtle concurrency problems can’t be reliably duplicated by running the code.

Once you are finished reading this book, you should be ready to:
Start simplyWrite automated testsRefactor to add design decisions one at a time

This book is organized into three sections.
An example of writing typical model code using TDD. The example is one I got from Ward Cunningham years ago, and have used many times since, multi-currency arithmetic. In it you will learn to write tests before code and grow a design organically.An example of testing more complicated logic, including reflection and exceptions, by developing a framework for automated testing. This example also serves to introduce you to the xUnit architecture that is at the heart of many programmer-oriented testing tools. In the second example you will learn to work in even smaller steps than in the first example, including the kind of self-referential hooha beloved of computer scientists.Patterns for TDD. Included are patterns for the deciding what tests to write, how to write tests using xUnit, and a greatest hits selection of the design patterns and refactorings used in the examples.

I wrote the examples imagining a pair programming session. If you like looking at the map before wandering around, you may want to go straight to the patterns in Section 3 and use the examples as illustrations. If you prefer just wandering around and then looking at the map to see where you’ve been, try reading the examples through and refering to the patterns when you want more detail about a technique, then using the patterns as a reference.

Several reviewers have commented they got the most out of the examples when they started up a programming environment and entered the code and ran the tests as they read.

A note about the examples. Both examples, multi-currency calculation and a testing framework, appear simple. There are (and I have seen) complicated, ugly, messy ways of solving the same problems. I could have chosen one of those complicated, ugly, messy solutions to give the book an air of “reality.” However, my goal, and I hope your goal, is to write clean code that works. Before teeing off on the examples as being too simple, spend 15 seconds imagining a programming world in which all code was this clear and direct, where there were no complicated solutions, only apparently complicated problems begging for careful thought. TDD is a practice that can help you lead yourself to exactly that careful thought.

Test Driven Development: By Example

The 5th generation (5G) of mobile radio access technologies is expected to become available for commercial launch around 2020. In this paper, we present our envisioned 5G system design optimized for small cell deployment taking a clean slate approach, i.e. removing most compatibility constraints with the previous generations of mobile radio access technologies. This paper mainly covers the physical layer aspects of the 5G concept design.

/pdf/5g-small-cell-optimized-radio-design-2g27den37b.pdf

5G small cell optimized radio design

Ultra-dense small cells are foreseen to play an essential role in the 5th generation (5G) of mobile radio access technology, which will be operating over different bands with respect to established systems. The natural step for exploring new spectrum is to look into the centimeter-wave bands as well as exploring millimeter-wave bands. This paper presents our vision on the technology components for a 5G centimeter-wave concept for ultra-dense small cells. Fundamental features such as optimized short frame structure, multi-antenna technologies, interference rejection, rank adaptation and dynamic scheduling of uplink/downlink transmission are discussed, along with the design of a novel flexible waveform and energy-saving enablers.

/pdf/centimeter-wave-concept-for-5g-ultra-dense-small-cells-2bmodezy9d.pdf

Centimeter-Wave Concept for 5G Ultra-Dense Small Cells

Compared to the previous generations of mobile networks, 5G will provide a significant paradigm shift by including beyond state of the art technical solutions, like very high carrier frequencies with massive bandwidths, extreme base station and device densities, and very high number of transceiver antennas. However, unlike the previous generations, it will also be highly integrative and backward compatible: combining the novel 5G air interface and spectrum together with legacy wireless systems like LTE/LTE-A and WiFi, in order to facilitate an umbrella of high-rate coverage and a seamless user experience. In order to support this advances in the radio interface, the core network will also have to reach unprecedented levels of elasticity and intelligence. Spectrum regulation will need to be rethought and significantly improved, whereas energy and cost efficiencies will become one of the key parameters that will steer the 5G design and development. This paper elaborates on the 5G related topics, identifying the key challenges for future research and preliminary 5G standardization activities, as well as providing a comprehensive survey of the current literature.

Visions Towards 5G: Technical Requirements and Potential Enablers

This chapter contains sections titled: Introduction Principles of QAM-OFDM Modulation by DFT Transmission via Bandlimited Channels Generalised Nyquist Criterion Basic OFDM Modem Implementations Cyclic OFDM Symbol Extension Reducing MDI by Compensation [15] Decision-Directed Adaptive Channel Equalisation OFDM Bandwidth Efficiency Chapter Summary and Conclusion

Introduction to OFDMOFDM and MCCDMA for Broadband Multiuser Communications WLANS and Broadcasting. L.Hanzo, Mnster, T. Keller and B.J. Choi,

The Universal Software Radio Peripheral (USRP) developed by Ettus research is emerging as one of the most promising hardware solution for building a Software Defined Radio (SDR) platform. Originally designed for supporting GNU radio, it can also be interfaced to customized C++ code, thus allowing a higher degree of flexibility in the design of the transceiver chain. In this paper we describe the implementation of a coded Orthogonal Frequency Division Multiplexing (OFDM) transceiver running over USRP2 boards. The baseband processing and the radio-frequency settings are designed for coping with a local area scenario as well as with the physical capabilities of the USRP2 boards. Moreover, a simple subcarrier blinding algorithm is proposed with the aim of compensating the common phase error in the symbol constellation due to the limited nominal accuracy of the local oscillators. Performance results show the effectiveness of the proposed architecture and settings for achieving Block Error Rate (BLER) results below 1% at 12 dB of Signal-to-Noise Ratio (SNR) without requiring a high precision reference clock.

An SDR architecture for OFDM transmission over USRP2 boards

The exponential growth in indoor data traffic necessitates a massive deployment of small cells, and emphasizes the importance of interference coordination and suppression to realize the full potential of this densification. To be effective however, interference coordination and suppression requires strict time synchronization between the cells. This paper deals with distributed runtime synchronization for Beyond 4G femtocells. A simple random scheduling solution for the clock distribution messages is proposed, as well as different clock update mechanisms. Simulation results for a dense cell scenario with two stripes of apartments show that a `multiplicative clock update' exhibits an initial large time divergence among neighbor cells, but is able to achieve a lower long-term error floor than `additive clock update'. Practical implications of the residual time misalignment on the Beyond 4G system design are also addressed.

/pdf/distributed-synchronization-for-beyond-4g-indoor-femtocells-4djciiuacb.pdf

Distributed synchronization for beyond 4G indoor femtocells

Evolution of Cognitive Networks and Self-Adaptive Communication Systems

The Interference Rejection Combining (IRC) receiver can significantly boost the network throughput in scenarios characterized by dense uncoordinated deployment of small cells, as targeted by future 5th generation (5G) radio access technology. This paper presents an experimental study on the potential benefit of IRC receiver in real deployment scenarios. The study is carried out using a software defined radio (SDR) testbed network with four cells, each featuring one Access Point (AP) and one User Equipment (UE) with two antennas. The testbed network was placed in an indoor office and open hall scenarios, respectively. In each scenario, the cells were arranged to characterize the propagation in different spatial configurations. Using the obtained propagation data, we analysed the cases of closed and open subscriber group for the respective scenarios, to compare the achievable throughput with IRC and Maximum Ratio Combining (MRC) receivers. Different frequency reuse schemes were also considered. The throughput results confirm the effectiveness of the IRC receiver in improving the network throughput with respect to the MRC receiver, under the assumption of single stream (rank 1) transmission. Results show average gains up to around 40% and outage gains up to 70% over the MRC receiver. The combination of the IRC receiver and frequency reuse achieves a favourable trade-off between the network throughput and fairness. Overall, due to the direct propagation, the open hall open subscriber group scenario is benefiting the most from the ability of the IRC receiver to cancel a strong dominant interferer.

Experimental evaluation of interference rejection combining for 5G small cells

The evolution of wireless communications is bringing into reality the dense deployment of femto and local area cells, which represents a challenging scenario for proving the effectiveness of Cognitive Radio (CR) frameworks. In particular the Dynamic Spectrum Allocation (DSA) paradigm aims at solving the resource allocation problem in a fully autonomous way. While in both CR and standardization lot of effort has been spent in developing efficient DSA algorithms, their research-oriented software radio implementation is still disregarded. In this paper, the design approach used for the definition of a CR-based, local area-oriented testbed platform is introduced. In particular, the testbed design in relation to the selected scenario and the architecture of the developed software framework are presented. An analysis of the performance of key software functionalities is also provided: preliminary results show a computational load compatible with nowadays Commercial-Off-The-Shelf computers.

Oscar Tonelli

Papers

An SDR architecture for OFDM transmission over USRP2 boards

Distributed synchronization for beyond 4G indoor femtocells

Evolution of Cognitive Networks and Self-Adaptive Communication Systems

Experimental evaluation of interference rejection combining for 5G small cells

Software architecture design for a Dynamic Spectrum Allocation-enabled Cognitive Radio testbed